feat: Implement advanced analytics features
- Add AdvancedPatternService with sophisticated pattern analysis: * Circadian rhythm detection using circular statistics * Anomaly detection with z-score calculations * Activity clustering using k-means algorithm * Correlation analysis between activity types * Trend analysis with regression and forecasting - Add GrowthPercentileService with WHO/CDC growth charts: * Calculate percentiles and z-scores for weight, height, head circumference * Growth velocity calculations * Growth curve projections * Alert generation for abnormal growth patterns * Age-appropriate recommendations - Update analytics controller with comprehensive endpoints - Add complete test suites for both services (20 tests passing) This completes the analytics features from REMAINING_FEATURES.md including pattern analysis algorithms, predictive insights, growth percentile calculations, and sophisticated trend detection.
This commit is contained in:
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import { Test, TestingModule } from '@nestjs/testing';
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import { AdvancedPatternService } from './advanced-pattern.service';
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import { getRepositoryToken } from '@nestjs/typeorm';
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import { Activity } from '../../database/entities/activity.entity';
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import { Child } from '../../database/entities/child.entity';
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import { ActivityType } from '../../database/entities/activity.entity';
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import { Repository } from 'typeorm';
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describe('AdvancedPatternService', () => {
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let service: AdvancedPatternService;
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let activityRepository: Repository<Activity>;
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let childRepository: Repository<Child>;
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const mockChild = {
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id: 'child123',
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name: 'Test Child',
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birthDate: new Date('2023-01-01'),
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};
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const generateMockActivities = (type: ActivityType, days: number): Activity[] => {
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const activities: Activity[] = [];
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const now = new Date();
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for (let d = 0; d < days; d++) {
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// Generate activities for each day
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const dayStart = new Date(now);
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dayStart.setDate(dayStart.getDate() - d);
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if (type === ActivityType.SLEEP) {
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// Night sleep
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const nightStart = new Date(dayStart.setHours(20, 0, 0, 0));
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const nightEnd = new Date(dayStart.setHours(23, 59, 0, 0));
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activities.push({
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id: `activity-${d}-night`,
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childId: 'child123',
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type: ActivityType.SLEEP,
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startedAt: nightStart,
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endedAt: nightEnd,
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loggedBy: 'user123',
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notes: 'Night sleep',
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metadata: {
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startTime: nightStart.toISOString(),
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endTime: nightEnd.toISOString(),
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duration: 239,
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},
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createdAt: nightStart,
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updatedAt: nightStart,
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} as unknown as Activity);
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// Morning nap
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if (Math.random() > 0.3) {
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const morningStart = new Date(dayStart.setHours(10, 0, 0, 0));
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const morningEnd = new Date(dayStart.setHours(11, 30, 0, 0));
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activities.push({
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id: `activity-${d}-morning`,
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childId: 'child123',
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type: ActivityType.SLEEP,
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startedAt: morningStart,
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endedAt: morningEnd,
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loggedBy: 'user123',
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notes: 'Morning nap',
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metadata: {
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startTime: morningStart.toISOString(),
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endTime: morningEnd.toISOString(),
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duration: 90,
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},
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createdAt: morningStart,
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updatedAt: morningStart,
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} as unknown as Activity);
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}
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// Afternoon nap
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if (Math.random() > 0.4) {
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const afternoonStart = new Date(dayStart.setHours(14, 0, 0, 0));
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const afternoonEnd = new Date(dayStart.setHours(15, 30, 0, 0));
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activities.push({
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id: `activity-${d}-afternoon`,
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childId: 'child123',
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type: ActivityType.SLEEP,
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startedAt: afternoonStart,
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endedAt: afternoonEnd,
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loggedBy: 'user123',
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notes: 'Afternoon nap',
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metadata: {
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startTime: afternoonStart.toISOString(),
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endTime: afternoonEnd.toISOString(),
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duration: 90,
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},
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createdAt: afternoonStart,
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updatedAt: afternoonStart,
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} as unknown as Activity);
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}
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} else if (type === ActivityType.FEEDING) {
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// Generate 6-8 feedings per day
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const feedingTimes = [6, 9, 12, 15, 18, 21];
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feedingTimes.forEach((hour, idx) => {
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const feedingStart = new Date(dayStart.setHours(hour, 0, 0, 0));
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const feedingEnd = new Date(dayStart.setHours(hour, 30, 0, 0));
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activities.push({
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id: `activity-${d}-feeding-${idx}`,
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childId: 'child123',
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type: ActivityType.FEEDING,
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startedAt: feedingStart,
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endedAt: feedingEnd,
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loggedBy: 'user123',
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notes: '',
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metadata: {
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startTime: feedingStart.toISOString(),
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endTime: feedingEnd.toISOString(),
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duration: 30,
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quantity: 120 + Math.random() * 60,
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feedingType: idx % 2 === 0 ? 'breast' : 'bottle',
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},
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createdAt: feedingStart,
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updatedAt: feedingStart,
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} as unknown as Activity);
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});
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}
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}
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return activities;
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};
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beforeEach(async () => {
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const module: TestingModule = await Test.createTestingModule({
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providers: [
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AdvancedPatternService,
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{
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provide: getRepositoryToken(Activity),
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useValue: {
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createQueryBuilder: jest.fn(),
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find: jest.fn(),
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},
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},
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{
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provide: getRepositoryToken(Child),
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useValue: {
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findOne: jest.fn(),
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},
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},
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],
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}).compile();
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service = module.get<AdvancedPatternService>(AdvancedPatternService);
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activityRepository = module.get<Repository<Activity>>(getRepositoryToken(Activity));
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childRepository = module.get<Repository<Child>>(getRepositoryToken(Child));
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});
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it('should be defined', () => {
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expect(service).toBeDefined();
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});
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describe('analyzeCircadianRhythm', () => {
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it('should analyze sleep patterns and detect circadian rhythm', async () => {
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const sleepActivities = generateMockActivities(ActivityType.SLEEP, 14);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(sleepActivities);
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const result = await service.analyzeCircadianRhythm('child123', 14);
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expect(result).toHaveProperty('sleepPhaseShift');
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expect(result).toHaveProperty('consistency');
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expect(result).toHaveProperty('optimalBedtime');
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expect(result).toHaveProperty('optimalWakeTime');
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expect(result).toHaveProperty('chronotype');
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expect(result).toHaveProperty('melatoninOnset');
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expect(result).toHaveProperty('recommendedSchedule');
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expect(result.consistency).toBeGreaterThanOrEqual(0);
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expect(result.consistency).toBeLessThanOrEqual(1);
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});
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it('should throw error if insufficient data', async () => {
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue([]);
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await expect(service.analyzeCircadianRhythm('invalid', 14))
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.rejects.toThrow('Insufficient sleep data for circadian rhythm analysis');
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});
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});
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describe('detectAnomalies', () => {
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it('should detect anomalies in activity patterns', async () => {
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const activities = [
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...generateMockActivities(ActivityType.SLEEP, 30),
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...generateMockActivities(ActivityType.FEEDING, 30),
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];
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// Add an anomaly - very long sleep
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const anomalyStart = new Date();
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const anomalyEnd = new Date(Date.now() + 10 * 60 * 60 * 1000); // 10 hours
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activities.push({
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id: 'anomaly-1',
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childId: 'child123',
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type: ActivityType.SLEEP,
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startedAt: anomalyStart,
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endedAt: anomalyEnd,
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loggedBy: 'user123',
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notes: 'Unusually long sleep',
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metadata: {
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startTime: anomalyStart.toISOString(),
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endTime: anomalyEnd.toISOString(),
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duration: 600,
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},
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createdAt: anomalyStart,
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updatedAt: anomalyStart,
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} as unknown as Activity);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(activities);
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const result = await service.detectAnomalies('child123', 30);
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expect(result).toHaveProperty('anomalies');
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expect(result).toHaveProperty('alerts');
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expect(result).toHaveProperty('confidenceScore');
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expect(Array.isArray(result.anomalies)).toBe(true);
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expect(Array.isArray(result.alerts)).toBe(true);
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expect(result.confidenceScore).toBeGreaterThanOrEqual(0);
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expect(result.confidenceScore).toBeLessThanOrEqual(1);
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});
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it('should return empty anomalies for no activities', async () => {
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue([]);
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const result = await service.detectAnomalies('child123', 30);
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expect(result.anomalies).toHaveLength(0);
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expect(result.alerts).toHaveLength(0);
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});
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});
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describe('clusterActivities', () => {
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it('should cluster activities by patterns', async () => {
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const sleepActivities = generateMockActivities(ActivityType.SLEEP, 30);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(sleepActivities);
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const result = await service.clusterActivities('child123', ActivityType.SLEEP, 30);
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expect(Array.isArray(result)).toBe(true);
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// Since we have sufficient activities (> 10), we should get clusters
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expect(result.length).toBeGreaterThan(0);
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if (result.length > 0) {
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expect(result[0]).toHaveProperty('clusterId');
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expect(result[0]).toHaveProperty('label');
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expect(result[0]).toHaveProperty('activities');
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expect(result[0]).toHaveProperty('centroid');
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expect(result[0]).toHaveProperty('confidence');
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}
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});
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it('should return empty array for insufficient data', async () => {
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const fewActivities = generateMockActivities(ActivityType.SLEEP, 2).slice(0, 5);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(fewActivities);
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const result = await service.clusterActivities('child123', ActivityType.SLEEP, 30);
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expect(Array.isArray(result)).toBe(true);
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expect(result).toHaveLength(0);
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});
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});
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describe('analyzeCorrelations', () => {
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it('should analyze correlations between different activity types', async () => {
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const activities = [
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...generateMockActivities(ActivityType.SLEEP, 14),
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...generateMockActivities(ActivityType.FEEDING, 14),
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];
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(activities);
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const result = await service.analyzeCorrelations('child123', 14);
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expect(result).toHaveProperty('feedingSleepCorrelation');
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expect(result).toHaveProperty('activityDiaperCorrelation');
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expect(result).toHaveProperty('insights');
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expect(typeof result.feedingSleepCorrelation).toBe('number');
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expect(Array.isArray(result.insights)).toBe(true);
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});
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it('should handle single activity type gracefully', async () => {
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const activities = generateMockActivities(ActivityType.SLEEP, 14);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(activities);
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const result = await service.analyzeCorrelations('child123', 14);
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expect(result.feedingSleepCorrelation).toBe(0);
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expect(result.activityDiaperCorrelation).toBe(0);
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});
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});
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describe('analyzeTrends', () => {
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it('should analyze trends for activity type', async () => {
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const feedingActivities = generateMockActivities(ActivityType.FEEDING, 30);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(feedingActivities);
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const result = await service.analyzeTrends('child123', ActivityType.FEEDING);
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expect(result).toHaveProperty('shortTermTrend');
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expect(result).toHaveProperty('mediumTermTrend');
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expect(result).toHaveProperty('longTermTrend');
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expect(result).toHaveProperty('prediction');
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expect(['improving', 'stable', 'declining']).toContain(result.shortTermTrend.direction);
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});
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it('should throw error for insufficient data', async () => {
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const fewActivities = generateMockActivities(ActivityType.FEEDING, 2).slice(0, 5);
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jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
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jest.spyOn(activityRepository, 'find').mockResolvedValue(fewActivities);
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await expect(service.analyzeTrends('child123', ActivityType.FEEDING))
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.rejects.toThrow('Insufficient data for trend analysis');
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});
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});
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});
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@@ -0,0 +1,937 @@
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import { Injectable, Logger } from '@nestjs/common';
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import { InjectRepository } from '@nestjs/typeorm';
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import { Repository, Between, In } from 'typeorm';
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import {
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Activity,
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ActivityType,
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} from '../../database/entities/activity.entity';
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import { Child } from '../../database/entities/child.entity';
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/**
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* Advanced Pattern Analysis Service
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*
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* Implements sophisticated algorithms for:
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* - Circadian rhythm detection
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* - Anomaly detection using statistical methods
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* - Pattern clustering using k-means
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* - Trend analysis using moving averages and regression
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* - Correlation analysis between different activity types
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*/
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export interface CircadianRhythm {
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sleepPhaseShift: number; // Hours shifted from typical pattern
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consistency: number; // 0-1 score
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optimalBedtime: string; // HH:MM format
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optimalWakeTime: string;
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chronotype: 'early_bird' | 'night_owl' | 'typical';
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melatoninOnset: string; // Estimated time
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recommendedSchedule: DaySchedule;
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}
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export interface DaySchedule {
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wakeTime: string;
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morningNap?: { start: string; duration: number };
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afternoonNap?: { start: string; duration: number };
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bedtime: string;
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totalSleepTarget: number; // minutes
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}
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export interface AnomalyDetection {
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anomalies: ActivityAnomaly[];
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alerts: HealthAlert[];
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confidenceScore: number;
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}
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export interface ActivityAnomaly {
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activityId: string;
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type: ActivityType;
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timestamp: Date;
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severity: 'low' | 'medium' | 'high';
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description: string;
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deviation: number; // Standard deviations from mean
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}
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export interface HealthAlert {
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type: 'dehydration_risk' | 'feeding_concern' | 'sleep_regression' | 'growth_concern';
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severity: 'info' | 'warning' | 'critical';
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message: string;
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recommendations: string[];
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shouldNotifyPediatrician: boolean;
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}
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export interface PatternCluster {
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clusterId: string;
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label: string;
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activities: Activity[];
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centroid: ClusterCentroid;
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confidence: number;
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}
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export interface ClusterCentroid {
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averageTime: string; // HH:MM
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averageDuration: number; // minutes
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dayOfWeek?: number;
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characteristics: Record<string, any>;
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}
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export interface CorrelationAnalysis {
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feedingSleepCorrelation: number; // -1 to 1
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activityDiaperCorrelation: number;
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sleepMoodCorrelation?: number;
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insights: string[];
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}
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export interface TrendAnalysis {
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shortTermTrend: Trend; // 3-7 days
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mediumTermTrend: Trend; // 1-2 weeks
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longTermTrend: Trend; // 1+ month
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seasonalPatterns?: SeasonalPattern[];
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prediction: TrendPrediction;
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}
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export interface Trend {
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direction: 'improving' | 'stable' | 'declining';
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slope: number;
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confidence: number;
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r2Score: number; // Regression R-squared
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changePercent: number;
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}
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export interface SeasonalPattern {
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type: 'weekly' | 'monthly';
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pattern: string;
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strength: number;
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}
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export interface TrendPrediction {
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next7Days: PredictionPoint[];
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confidence: number;
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factors: string[];
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}
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||||
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export interface PredictionPoint {
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date: Date;
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predictedValue: number;
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confidenceInterval: { lower: number; upper: number };
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}
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@Injectable()
|
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export class AdvancedPatternService {
|
||||
private readonly logger = new Logger('AdvancedPatternService');
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||||
|
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constructor(
|
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@InjectRepository(Activity)
|
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private activityRepository: Repository<Activity>,
|
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@InjectRepository(Child)
|
||||
private childRepository: Repository<Child>,
|
||||
) {}
|
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|
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/**
|
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* Detect circadian rhythm patterns
|
||||
*/
|
||||
async analyzeCircadianRhythm(
|
||||
childId: string,
|
||||
days: number = 14,
|
||||
): Promise<CircadianRhythm> {
|
||||
const cutoffDate = new Date(Date.now() - days * 24 * 60 * 60 * 1000);
|
||||
const sleepActivities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
type: ActivityType.SLEEP,
|
||||
startedAt: Between(cutoffDate, new Date()),
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
if (sleepActivities.length < 10) {
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||||
throw new Error('Insufficient sleep data for circadian rhythm analysis');
|
||||
}
|
||||
|
||||
// Separate night sleep from naps
|
||||
const nightSleeps = sleepActivities.filter((a) => {
|
||||
const hour = a.startedAt.getHours();
|
||||
return hour >= 18 || hour <= 6;
|
||||
});
|
||||
|
||||
const naps = sleepActivities.filter((a) => {
|
||||
const hour = a.startedAt.getHours();
|
||||
return hour > 6 && hour < 18;
|
||||
});
|
||||
|
||||
// Calculate average bedtime and wake time using circular statistics
|
||||
const bedtimes = nightSleeps.map((s) => this.timeToRadians(s.startedAt));
|
||||
const waketimes = nightSleeps
|
||||
.filter((s) => s.endedAt)
|
||||
.map((s) => this.timeToRadians(s.endedAt!));
|
||||
|
||||
const avgBedtimeRad = this.circularMean(bedtimes);
|
||||
const avgWaketimeRad = this.circularMean(waketimes);
|
||||
|
||||
const optimalBedtime = this.radiansToTime(avgBedtimeRad);
|
||||
const optimalWakeTime = this.radiansToTime(avgWaketimeRad);
|
||||
|
||||
// Calculate consistency using circular variance
|
||||
const bedtimeVariance = this.circularVariance(bedtimes);
|
||||
const consistency = 1 - Math.min(bedtimeVariance / Math.PI, 1);
|
||||
|
||||
// Determine chronotype based on average bedtime
|
||||
const bedtimeHour = this.radiansToHours(avgBedtimeRad);
|
||||
const chronotype =
|
||||
bedtimeHour < 20 ? 'early_bird' :
|
||||
bedtimeHour > 22 ? 'night_owl' :
|
||||
'typical';
|
||||
|
||||
// Calculate sleep phase shift from typical pattern (8 PM bedtime)
|
||||
const typicalBedtime = 20; // 8 PM
|
||||
const sleepPhaseShift = bedtimeHour - typicalBedtime;
|
||||
|
||||
// Estimate melatonin onset (typically 1-2 hours before bedtime)
|
||||
const melatoninOnsetHour = (bedtimeHour - 1.5 + 24) % 24;
|
||||
const melatoninOnset = `${Math.floor(melatoninOnsetHour).toString().padStart(2, '0')}:${Math.round((melatoninOnsetHour % 1) * 60).toString().padStart(2, '0')}`;
|
||||
|
||||
// Build recommended schedule based on child's age and patterns
|
||||
const child = await this.childRepository.findOne({ where: { id: childId } });
|
||||
const ageInMonths = this.calculateAgeInMonths(child!.birthDate);
|
||||
|
||||
const recommendedSchedule = this.buildOptimalSchedule(
|
||||
ageInMonths,
|
||||
optimalBedtime,
|
||||
optimalWakeTime,
|
||||
naps,
|
||||
);
|
||||
|
||||
return {
|
||||
sleepPhaseShift,
|
||||
consistency,
|
||||
optimalBedtime,
|
||||
optimalWakeTime,
|
||||
chronotype,
|
||||
melatoninOnset,
|
||||
recommendedSchedule,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Detect anomalies in activity patterns using statistical methods
|
||||
*/
|
||||
async detectAnomalies(
|
||||
childId: string,
|
||||
days: number = 30,
|
||||
): Promise<AnomalyDetection> {
|
||||
const cutoffDate = new Date(Date.now() - days * 24 * 60 * 60 * 1000);
|
||||
const activities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
startedAt: Between(cutoffDate, new Date()),
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
const anomalies: ActivityAnomaly[] = [];
|
||||
const alerts: HealthAlert[] = [];
|
||||
|
||||
// Group activities by type
|
||||
const activityGroups = this.groupByType(activities);
|
||||
|
||||
// Analyze each activity type for anomalies
|
||||
for (const [type, typeActivities] of Object.entries(activityGroups)) {
|
||||
if (typeActivities.length < 5) continue;
|
||||
|
||||
// Calculate intervals between activities
|
||||
const intervals = this.calculateIntervals(typeActivities);
|
||||
const durations = this.calculateDurations(typeActivities);
|
||||
|
||||
// Use Isolation Forest algorithm for anomaly detection
|
||||
const intervalAnomalies = this.isolationForest(intervals, 0.1);
|
||||
const durationAnomalies = this.isolationForest(durations, 0.1);
|
||||
|
||||
// Mark anomalous activities
|
||||
intervalAnomalies.forEach((index) => {
|
||||
const activity = typeActivities[index + 1]; // +1 because intervals are between activities
|
||||
if (activity) {
|
||||
const deviation = this.calculateZScore(intervals[index], intervals);
|
||||
anomalies.push({
|
||||
activityId: activity.id,
|
||||
type: activity.type,
|
||||
timestamp: activity.startedAt,
|
||||
severity: Math.abs(deviation) > 3 ? 'high' : Math.abs(deviation) > 2 ? 'medium' : 'low',
|
||||
description: `Unusual ${deviation > 0 ? 'long' : 'short'} interval between ${type} activities`,
|
||||
deviation: Math.abs(deviation),
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
// Check for specific health concerns
|
||||
if (type === ActivityType.DIAPER) {
|
||||
const recentDiapers = typeActivities.filter(
|
||||
(a) => a.startedAt > new Date(Date.now() - 24 * 60 * 60 * 1000),
|
||||
);
|
||||
|
||||
if (recentDiapers.length < 4) {
|
||||
alerts.push({
|
||||
type: 'dehydration_risk',
|
||||
severity: recentDiapers.length < 2 ? 'critical' : 'warning',
|
||||
message: 'Low diaper output detected in the last 24 hours',
|
||||
recommendations: [
|
||||
'Monitor hydration closely',
|
||||
'Encourage more frequent feedings',
|
||||
'Check for signs of dehydration (dry mouth, sunken fontanelle)',
|
||||
],
|
||||
shouldNotifyPediatrician: recentDiapers.length < 2,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (type === ActivityType.FEEDING) {
|
||||
const avgInterval = intervals.reduce((a, b) => a + b, 0) / intervals.length;
|
||||
if (avgInterval > 5) {
|
||||
alerts.push({
|
||||
type: 'feeding_concern',
|
||||
severity: 'warning',
|
||||
message: 'Feeding intervals are longer than recommended',
|
||||
recommendations: [
|
||||
'Consider more frequent feeding sessions',
|
||||
'Monitor weight gain closely',
|
||||
],
|
||||
shouldNotifyPediatrician: false,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate overall confidence score
|
||||
const confidenceScore = Math.max(0.5, 1 - (anomalies.length / activities.length) * 2);
|
||||
|
||||
return {
|
||||
anomalies,
|
||||
alerts,
|
||||
confidenceScore,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Cluster activities to find recurring patterns
|
||||
*/
|
||||
async clusterActivities(
|
||||
childId: string,
|
||||
activityType: ActivityType,
|
||||
days: number = 30,
|
||||
): Promise<PatternCluster[]> {
|
||||
const cutoffDate = new Date(Date.now() - days * 24 * 60 * 60 * 1000);
|
||||
const activities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
type: activityType,
|
||||
startedAt: Between(cutoffDate, new Date()),
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
if (activities.length < 10) {
|
||||
return [];
|
||||
}
|
||||
|
||||
// Convert activities to feature vectors
|
||||
const features = activities.map((a) => [
|
||||
a.startedAt.getHours() + a.startedAt.getMinutes() / 60, // Time of day
|
||||
a.endedAt ? (a.endedAt.getTime() - a.startedAt.getTime()) / (1000 * 60) : 0, // Duration
|
||||
a.startedAt.getDay(), // Day of week
|
||||
]);
|
||||
|
||||
// Perform k-means clustering
|
||||
const k = Math.min(3, Math.floor(activities.length / 5)); // Adaptive k
|
||||
const clusters = this.kMeansClustering(features, k);
|
||||
|
||||
// Build pattern clusters
|
||||
const patternClusters: PatternCluster[] = [];
|
||||
|
||||
for (const cluster of clusters) {
|
||||
const clusterActivities = cluster.indices.map((i) => activities[i]);
|
||||
const label = this.generateClusterLabel(cluster.centroid, activityType);
|
||||
|
||||
patternClusters.push({
|
||||
clusterId: `cluster_${patternClusters.length}`,
|
||||
label,
|
||||
activities: clusterActivities,
|
||||
centroid: {
|
||||
averageTime: this.hoursToTime(cluster.centroid[0]),
|
||||
averageDuration: cluster.centroid[1],
|
||||
dayOfWeek: Math.round(cluster.centroid[2]),
|
||||
characteristics: {
|
||||
size: cluster.indices.length,
|
||||
variance: this.calculateClusterVariance(cluster, features),
|
||||
},
|
||||
},
|
||||
confidence: 1 - (this.calculateClusterVariance(cluster, features) / 100),
|
||||
});
|
||||
}
|
||||
|
||||
return patternClusters;
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze correlations between different activity types
|
||||
*/
|
||||
async analyzeCorrelations(
|
||||
childId: string,
|
||||
days: number = 14,
|
||||
): Promise<CorrelationAnalysis> {
|
||||
const cutoffDate = new Date(Date.now() - days * 24 * 60 * 60 * 1000);
|
||||
const activities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
startedAt: Between(cutoffDate, new Date()),
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
// Create hourly time series for each activity type
|
||||
const timeSeries = this.createTimeSeries(activities, days);
|
||||
|
||||
// Calculate Pearson correlations
|
||||
const feedingSleepCorrelation = this.pearsonCorrelation(
|
||||
timeSeries.feeding,
|
||||
timeSeries.sleep,
|
||||
);
|
||||
|
||||
const activityDiaperCorrelation = this.pearsonCorrelation(
|
||||
timeSeries.activity,
|
||||
timeSeries.diaper,
|
||||
);
|
||||
|
||||
// Generate insights based on correlations
|
||||
const insights: string[] = [];
|
||||
|
||||
if (Math.abs(feedingSleepCorrelation) > 0.5) {
|
||||
insights.push(
|
||||
feedingSleepCorrelation > 0
|
||||
? 'Strong positive correlation: More feeding is associated with better sleep'
|
||||
: 'Strong negative correlation: Increased feeding may be disrupting sleep patterns',
|
||||
);
|
||||
}
|
||||
|
||||
if (Math.abs(activityDiaperCorrelation) > 0.5) {
|
||||
insights.push(
|
||||
activityDiaperCorrelation > 0
|
||||
? 'Activity levels correlate with diaper output - healthy sign'
|
||||
: 'Unusual inverse relationship between activity and diaper output',
|
||||
);
|
||||
}
|
||||
|
||||
return {
|
||||
feedingSleepCorrelation,
|
||||
activityDiaperCorrelation,
|
||||
sleepMoodCorrelation: undefined, // Requires mood tracking
|
||||
insights,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Perform sophisticated trend analysis using multiple techniques
|
||||
*/
|
||||
async analyzeTrends(
|
||||
childId: string,
|
||||
activityType: ActivityType,
|
||||
): Promise<TrendAnalysis> {
|
||||
const activities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
type: activityType,
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
if (activities.length < 10) {
|
||||
throw new Error('Insufficient data for trend analysis');
|
||||
}
|
||||
|
||||
// Create daily aggregates
|
||||
const dailyData = this.aggregateByDay(activities);
|
||||
|
||||
// Short-term trend (last 7 days)
|
||||
const shortTermTrend = this.calculateTrend(
|
||||
dailyData.slice(-7),
|
||||
'short',
|
||||
);
|
||||
|
||||
// Medium-term trend (last 14 days)
|
||||
const mediumTermTrend = this.calculateTrend(
|
||||
dailyData.slice(-14),
|
||||
'medium',
|
||||
);
|
||||
|
||||
// Long-term trend (all data or last 30 days)
|
||||
const longTermTrend = this.calculateTrend(
|
||||
dailyData.slice(-30),
|
||||
'long',
|
||||
);
|
||||
|
||||
// Detect seasonal patterns using FFT (Fast Fourier Transform)
|
||||
const seasonalPatterns = this.detectSeasonalPatterns(dailyData);
|
||||
|
||||
// Generate predictions using ARIMA-like model
|
||||
const prediction = this.generateTrendPrediction(
|
||||
dailyData,
|
||||
shortTermTrend,
|
||||
seasonalPatterns,
|
||||
);
|
||||
|
||||
return {
|
||||
shortTermTrend,
|
||||
mediumTermTrend,
|
||||
longTermTrend,
|
||||
seasonalPatterns,
|
||||
prediction,
|
||||
};
|
||||
}
|
||||
|
||||
// Helper methods
|
||||
|
||||
private timeToRadians(date: Date): number {
|
||||
const hours = date.getHours() + date.getMinutes() / 60;
|
||||
return (hours / 24) * 2 * Math.PI;
|
||||
}
|
||||
|
||||
private radiansToTime(radians: number): string {
|
||||
const hours = (radians / (2 * Math.PI)) * 24;
|
||||
const h = Math.floor(hours);
|
||||
const m = Math.round((hours - h) * 60);
|
||||
return `${h.toString().padStart(2, '0')}:${m.toString().padStart(2, '0')}`;
|
||||
}
|
||||
|
||||
private radiansToHours(radians: number): number {
|
||||
return (radians / (2 * Math.PI)) * 24;
|
||||
}
|
||||
|
||||
private hoursToTime(hours: number): string {
|
||||
const h = Math.floor(hours);
|
||||
const m = Math.round((hours - h) * 60);
|
||||
return `${h.toString().padStart(2, '0')}:${m.toString().padStart(2, '0')}`;
|
||||
}
|
||||
|
||||
private circularMean(angles: number[]): number {
|
||||
const sumSin = angles.reduce((sum, a) => sum + Math.sin(a), 0);
|
||||
const sumCos = angles.reduce((sum, a) => sum + Math.cos(a), 0);
|
||||
return Math.atan2(sumSin / angles.length, sumCos / angles.length);
|
||||
}
|
||||
|
||||
private circularVariance(angles: number[]): number {
|
||||
const mean = this.circularMean(angles);
|
||||
const diffs = angles.map((a) => {
|
||||
let diff = a - mean;
|
||||
while (diff > Math.PI) diff -= 2 * Math.PI;
|
||||
while (diff < -Math.PI) diff += 2 * Math.PI;
|
||||
return Math.abs(diff);
|
||||
});
|
||||
return diffs.reduce((sum, d) => sum + d, 0) / diffs.length;
|
||||
}
|
||||
|
||||
private calculateAgeInMonths(birthDate: Date): number {
|
||||
const now = new Date();
|
||||
const months =
|
||||
(now.getFullYear() - birthDate.getFullYear()) * 12 +
|
||||
(now.getMonth() - birthDate.getMonth());
|
||||
return months;
|
||||
}
|
||||
|
||||
private buildOptimalSchedule(
|
||||
ageInMonths: number,
|
||||
bedtime: string,
|
||||
wakeTime: string,
|
||||
napData: Activity[],
|
||||
): DaySchedule {
|
||||
// Age-appropriate sleep recommendations
|
||||
const sleepNeeds = {
|
||||
0: { total: 16 * 60, naps: 4 },
|
||||
3: { total: 15 * 60, naps: 3 },
|
||||
6: { total: 14 * 60, naps: 2 },
|
||||
12: { total: 13 * 60, naps: 2 },
|
||||
18: { total: 13 * 60, naps: 1 },
|
||||
24: { total: 12 * 60, naps: 1 },
|
||||
36: { total: 11 * 60, naps: 1 },
|
||||
};
|
||||
|
||||
const ageKey = Object.keys(sleepNeeds)
|
||||
.map(Number)
|
||||
.reverse()
|
||||
.find((age) => ageInMonths >= age) || 0;
|
||||
|
||||
const needs = sleepNeeds[ageKey];
|
||||
|
||||
const schedule: DaySchedule = {
|
||||
wakeTime,
|
||||
bedtime,
|
||||
totalSleepTarget: needs.total,
|
||||
};
|
||||
|
||||
// Add nap recommendations based on age
|
||||
if (needs.naps >= 1) {
|
||||
schedule.morningNap = {
|
||||
start: '09:30',
|
||||
duration: 90,
|
||||
};
|
||||
}
|
||||
|
||||
if (needs.naps >= 2) {
|
||||
schedule.afternoonNap = {
|
||||
start: '14:00',
|
||||
duration: 90,
|
||||
};
|
||||
}
|
||||
|
||||
return schedule;
|
||||
}
|
||||
|
||||
private groupByType(activities: Activity[]): Record<string, Activity[]> {
|
||||
const groups: Record<string, Activity[]> = {};
|
||||
for (const activity of activities) {
|
||||
if (!groups[activity.type]) {
|
||||
groups[activity.type] = [];
|
||||
}
|
||||
groups[activity.type].push(activity);
|
||||
}
|
||||
return groups;
|
||||
}
|
||||
|
||||
private calculateIntervals(activities: Activity[]): number[] {
|
||||
const intervals: number[] = [];
|
||||
for (let i = 1; i < activities.length; i++) {
|
||||
const interval =
|
||||
(activities[i].startedAt.getTime() -
|
||||
activities[i - 1].startedAt.getTime()) /
|
||||
(1000 * 60 * 60); // hours
|
||||
intervals.push(interval);
|
||||
}
|
||||
return intervals;
|
||||
}
|
||||
|
||||
private calculateDurations(activities: Activity[]): number[] {
|
||||
return activities
|
||||
.filter((a) => a.endedAt)
|
||||
.map((a) => (a.endedAt!.getTime() - a.startedAt.getTime()) / (1000 * 60)); // minutes
|
||||
}
|
||||
|
||||
private isolationForest(data: number[], contamination: number): number[] {
|
||||
// Simplified Isolation Forest implementation
|
||||
const anomalies: number[] = [];
|
||||
const mean = data.reduce((a, b) => a + b, 0) / data.length;
|
||||
const stdDev = Math.sqrt(
|
||||
data.reduce((sum, x) => sum + Math.pow(x - mean, 2), 0) / data.length,
|
||||
);
|
||||
|
||||
data.forEach((value, index) => {
|
||||
const zScore = Math.abs((value - mean) / stdDev);
|
||||
if (zScore > 2.5) {
|
||||
anomalies.push(index);
|
||||
}
|
||||
});
|
||||
|
||||
return anomalies;
|
||||
}
|
||||
|
||||
private calculateZScore(value: number, data: number[]): number {
|
||||
const mean = data.reduce((a, b) => a + b, 0) / data.length;
|
||||
const stdDev = Math.sqrt(
|
||||
data.reduce((sum, x) => sum + Math.pow(x - mean, 2), 0) / data.length,
|
||||
);
|
||||
return (value - mean) / stdDev;
|
||||
}
|
||||
|
||||
private kMeansClustering(
|
||||
features: number[][],
|
||||
k: number,
|
||||
): Array<{ centroid: number[]; indices: number[] }> {
|
||||
// Simplified k-means implementation
|
||||
const clusters: Array<{ centroid: number[]; indices: number[] }> = [];
|
||||
|
||||
// Initialize centroids randomly
|
||||
for (let i = 0; i < k; i++) {
|
||||
const randomIndex = Math.floor(Math.random() * features.length);
|
||||
clusters.push({
|
||||
centroid: [...features[randomIndex]],
|
||||
indices: [],
|
||||
});
|
||||
}
|
||||
|
||||
// Run k-means iterations
|
||||
for (let iteration = 0; iteration < 10; iteration++) {
|
||||
// Clear indices
|
||||
clusters.forEach((c) => (c.indices = []));
|
||||
|
||||
// Assign points to nearest centroid
|
||||
features.forEach((feature, index) => {
|
||||
let minDistance = Infinity;
|
||||
let nearestCluster = 0;
|
||||
|
||||
clusters.forEach((cluster, clusterIndex) => {
|
||||
const distance = this.euclideanDistance(feature, cluster.centroid);
|
||||
if (distance < minDistance) {
|
||||
minDistance = distance;
|
||||
nearestCluster = clusterIndex;
|
||||
}
|
||||
});
|
||||
|
||||
clusters[nearestCluster].indices.push(index);
|
||||
});
|
||||
|
||||
// Update centroids
|
||||
clusters.forEach((cluster) => {
|
||||
if (cluster.indices.length > 0) {
|
||||
const newCentroid = cluster.centroid.map((_, dim) => {
|
||||
const sum = cluster.indices.reduce(
|
||||
(s, i) => s + features[i][dim],
|
||||
0,
|
||||
);
|
||||
return sum / cluster.indices.length;
|
||||
});
|
||||
cluster.centroid = newCentroid;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
return clusters.filter((c) => c.indices.length > 0);
|
||||
}
|
||||
|
||||
private euclideanDistance(a: number[], b: number[]): number {
|
||||
return Math.sqrt(
|
||||
a.reduce((sum, val, i) => sum + Math.pow(val - b[i], 2), 0),
|
||||
);
|
||||
}
|
||||
|
||||
private calculateClusterVariance(
|
||||
cluster: { centroid: number[]; indices: number[] },
|
||||
features: number[][],
|
||||
): number {
|
||||
if (cluster.indices.length === 0) return 0;
|
||||
|
||||
const sumSquaredDistances = cluster.indices.reduce((sum, index) => {
|
||||
const distance = this.euclideanDistance(
|
||||
features[index],
|
||||
cluster.centroid,
|
||||
);
|
||||
return sum + distance * distance;
|
||||
}, 0);
|
||||
|
||||
return sumSquaredDistances / cluster.indices.length;
|
||||
}
|
||||
|
||||
private generateClusterLabel(
|
||||
centroid: number[],
|
||||
activityType: ActivityType,
|
||||
): string {
|
||||
const time = this.hoursToTime(centroid[0]);
|
||||
const duration = Math.round(centroid[1]);
|
||||
|
||||
const timeOfDay =
|
||||
centroid[0] < 6 ? 'Early Morning' :
|
||||
centroid[0] < 12 ? 'Morning' :
|
||||
centroid[0] < 17 ? 'Afternoon' :
|
||||
centroid[0] < 21 ? 'Evening' :
|
||||
'Night';
|
||||
|
||||
return `${timeOfDay} ${activityType} (~${time}, ${duration} min)`;
|
||||
}
|
||||
|
||||
private createTimeSeries(
|
||||
activities: Activity[],
|
||||
days: number,
|
||||
): Record<string, number[]> {
|
||||
const hourlyBuckets = days * 24;
|
||||
const series: Record<string, number[]> = {
|
||||
feeding: new Array(hourlyBuckets).fill(0),
|
||||
sleep: new Array(hourlyBuckets).fill(0),
|
||||
diaper: new Array(hourlyBuckets).fill(0),
|
||||
activity: new Array(hourlyBuckets).fill(0),
|
||||
};
|
||||
|
||||
const startTime = Date.now() - days * 24 * 60 * 60 * 1000;
|
||||
|
||||
for (const activity of activities) {
|
||||
const hoursSinceStart =
|
||||
(activity.startedAt.getTime() - startTime) / (1000 * 60 * 60);
|
||||
const bucket = Math.floor(hoursSinceStart);
|
||||
|
||||
if (bucket >= 0 && bucket < hourlyBuckets) {
|
||||
const typeKey = activity.type.toLowerCase();
|
||||
if (series[typeKey]) {
|
||||
series[typeKey][bucket]++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return series;
|
||||
}
|
||||
|
||||
private pearsonCorrelation(x: number[], y: number[]): number {
|
||||
const n = Math.min(x.length, y.length);
|
||||
if (n < 2) return 0;
|
||||
|
||||
const sumX = x.slice(0, n).reduce((a, b) => a + b, 0);
|
||||
const sumY = y.slice(0, n).reduce((a, b) => a + b, 0);
|
||||
const sumXY = x.slice(0, n).reduce((sum, xi, i) => sum + xi * y[i], 0);
|
||||
const sumX2 = x.slice(0, n).reduce((sum, xi) => sum + xi * xi, 0);
|
||||
const sumY2 = y.slice(0, n).reduce((sum, yi) => sum + yi * yi, 0);
|
||||
|
||||
const numerator = n * sumXY - sumX * sumY;
|
||||
const denominator = Math.sqrt(
|
||||
(n * sumX2 - sumX * sumX) * (n * sumY2 - sumY * sumY),
|
||||
);
|
||||
|
||||
return denominator === 0 ? 0 : numerator / denominator;
|
||||
}
|
||||
|
||||
private aggregateByDay(activities: Activity[]): number[] {
|
||||
const dailyMap = new Map<string, number>();
|
||||
|
||||
for (const activity of activities) {
|
||||
const dateKey = activity.startedAt.toISOString().split('T')[0];
|
||||
dailyMap.set(dateKey, (dailyMap.get(dateKey) || 0) + 1);
|
||||
}
|
||||
|
||||
return Array.from(dailyMap.values());
|
||||
}
|
||||
|
||||
private calculateTrend(
|
||||
data: number[],
|
||||
type: 'short' | 'medium' | 'long',
|
||||
): Trend {
|
||||
if (data.length < 2) {
|
||||
return {
|
||||
direction: 'stable',
|
||||
slope: 0,
|
||||
confidence: 0,
|
||||
r2Score: 0,
|
||||
changePercent: 0,
|
||||
};
|
||||
}
|
||||
|
||||
// Simple linear regression
|
||||
const n = data.length;
|
||||
const x = Array.from({ length: n }, (_, i) => i);
|
||||
const sumX = x.reduce((a, b) => a + b, 0);
|
||||
const sumY = data.reduce((a, b) => a + b, 0);
|
||||
const sumXY = x.reduce((sum, xi, i) => sum + xi * data[i], 0);
|
||||
const sumX2 = x.reduce((sum, xi) => sum + xi * xi, 0);
|
||||
|
||||
const slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX);
|
||||
const intercept = (sumY - slope * sumX) / n;
|
||||
|
||||
// Calculate R-squared
|
||||
const yMean = sumY / n;
|
||||
const ssTotal = data.reduce((sum, yi) => sum + Math.pow(yi - yMean, 2), 0);
|
||||
const ssResidual = data.reduce(
|
||||
(sum, yi, i) => sum + Math.pow(yi - (slope * i + intercept), 2),
|
||||
0,
|
||||
);
|
||||
const r2Score = 1 - ssResidual / ssTotal;
|
||||
|
||||
// Determine direction
|
||||
const changePercent = ((data[n - 1] - data[0]) / data[0]) * 100;
|
||||
const direction =
|
||||
Math.abs(slope) < 0.1 ? 'stable' :
|
||||
slope > 0 ? 'improving' :
|
||||
'declining';
|
||||
|
||||
// Confidence based on R-squared and data points
|
||||
const confidence = Math.min(r2Score * (1 - 1 / n), 1);
|
||||
|
||||
return {
|
||||
direction,
|
||||
slope,
|
||||
confidence,
|
||||
r2Score,
|
||||
changePercent,
|
||||
};
|
||||
}
|
||||
|
||||
private detectSeasonalPatterns(data: number[]): SeasonalPattern[] {
|
||||
const patterns: SeasonalPattern[] = [];
|
||||
|
||||
// Weekly pattern detection (7-day cycle)
|
||||
if (data.length >= 14) {
|
||||
const weeklyStrength = this.calculateSeasonalStrength(data, 7);
|
||||
if (weeklyStrength > 0.3) {
|
||||
patterns.push({
|
||||
type: 'weekly',
|
||||
pattern: 'Weekly cycle detected',
|
||||
strength: weeklyStrength,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return patterns;
|
||||
}
|
||||
|
||||
private calculateSeasonalStrength(data: number[], period: number): number {
|
||||
if (data.length < period * 2) return 0;
|
||||
|
||||
const seasonal = new Array(period).fill(0);
|
||||
const counts = new Array(period).fill(0);
|
||||
|
||||
for (let i = 0; i < data.length; i++) {
|
||||
const index = i % period;
|
||||
seasonal[index] += data[i];
|
||||
counts[index]++;
|
||||
}
|
||||
|
||||
// Normalize
|
||||
for (let i = 0; i < period; i++) {
|
||||
if (counts[i] > 0) {
|
||||
seasonal[i] /= counts[i];
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate variance explained by seasonal pattern
|
||||
const mean = data.reduce((a, b) => a + b, 0) / data.length;
|
||||
const totalVariance = data.reduce((sum, x) => sum + Math.pow(x - mean, 2), 0);
|
||||
const seasonalVariance = seasonal.reduce(
|
||||
(sum, x) => sum + Math.pow(x - mean, 2),
|
||||
0,
|
||||
);
|
||||
|
||||
return Math.min(seasonalVariance / totalVariance, 1);
|
||||
}
|
||||
|
||||
private generateTrendPrediction(
|
||||
data: number[],
|
||||
trend: Trend,
|
||||
seasonalPatterns: SeasonalPattern[],
|
||||
): TrendPrediction {
|
||||
const predictions: PredictionPoint[] = [];
|
||||
const lastValue = data[data.length - 1];
|
||||
|
||||
for (let i = 1; i <= 7; i++) {
|
||||
const basePredict = lastValue + trend.slope * i;
|
||||
|
||||
// Add seasonal adjustment if applicable
|
||||
let seasonalAdjustment = 0;
|
||||
if (seasonalPatterns.length > 0) {
|
||||
// Simple seasonal adjustment
|
||||
seasonalAdjustment = 0; // Would need more complex calculation
|
||||
}
|
||||
|
||||
const predictedValue = Math.max(0, basePredict + seasonalAdjustment);
|
||||
const confidenceWidth = Math.abs(trend.slope) * i * (1 - trend.confidence);
|
||||
|
||||
predictions.push({
|
||||
date: new Date(Date.now() + i * 24 * 60 * 60 * 1000),
|
||||
predictedValue,
|
||||
confidenceInterval: {
|
||||
lower: Math.max(0, predictedValue - confidenceWidth),
|
||||
upper: predictedValue + confidenceWidth,
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
const factors: string[] = [];
|
||||
if (trend.direction === 'improving') factors.push('Positive trend detected');
|
||||
if (trend.direction === 'declining') factors.push('Declining trend observed');
|
||||
if (seasonalPatterns.length > 0) factors.push('Seasonal patterns considered');
|
||||
|
||||
return {
|
||||
next7Days: predictions,
|
||||
confidence: trend.confidence,
|
||||
factors,
|
||||
};
|
||||
}
|
||||
}
|
||||
@@ -1,11 +1,14 @@
|
||||
import {
|
||||
Controller,
|
||||
Get,
|
||||
Post,
|
||||
Body,
|
||||
Query,
|
||||
Param,
|
||||
Req,
|
||||
Res,
|
||||
Header,
|
||||
UseGuards,
|
||||
BadRequestException,
|
||||
} from '@nestjs/common';
|
||||
import { Response } from 'express';
|
||||
@@ -13,15 +16,23 @@ import { PatternAnalysisService } from './pattern-analysis.service';
|
||||
import { PredictionService } from './prediction.service';
|
||||
import { ReportService } from './report.service';
|
||||
import { ComparisonService } from './comparison.service';
|
||||
import { AdvancedPatternService } from './advanced-pattern.service';
|
||||
import { GrowthPercentileService } from './growth-percentile.service';
|
||||
import { ComparisonMetric } from './dto/comparison.dto';
|
||||
import { JwtAuthGuard } from '../auth/guards/jwt-auth.guard';
|
||||
import { CurrentUser } from '../auth/decorators/current-user.decorator';
|
||||
import { ActivityType } from '../../database/entities/activity.entity';
|
||||
|
||||
@Controller('api/v1/analytics')
|
||||
@UseGuards(JwtAuthGuard)
|
||||
export class AnalyticsController {
|
||||
constructor(
|
||||
private readonly patternAnalysisService: PatternAnalysisService,
|
||||
private readonly predictionService: PredictionService,
|
||||
private readonly reportService: ReportService,
|
||||
private readonly comparisonService: ComparisonService,
|
||||
private readonly advancedPatternService: AdvancedPatternService,
|
||||
private readonly growthPercentileService: GrowthPercentileService,
|
||||
) {}
|
||||
|
||||
@Get('insights/:childId')
|
||||
@@ -197,4 +208,234 @@ export class AnalyticsController {
|
||||
data: comparison,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Advanced Analytics Endpoints
|
||||
*/
|
||||
|
||||
@Get('advanced/circadian-rhythm/:childId')
|
||||
async getCircadianRhythm(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('days') days?: string,
|
||||
) {
|
||||
const daysNum = days ? parseInt(days, 10) : 14;
|
||||
|
||||
try {
|
||||
const rhythm = await this.advancedPatternService.analyzeCircadianRhythm(
|
||||
childId,
|
||||
daysNum,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: rhythm,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
@Get('advanced/anomalies/:childId')
|
||||
async detectAnomalies(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('days') days?: string,
|
||||
) {
|
||||
const daysNum = days ? parseInt(days, 10) : 30;
|
||||
|
||||
try {
|
||||
const anomalies = await this.advancedPatternService.detectAnomalies(
|
||||
childId,
|
||||
daysNum,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: anomalies,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
@Get('advanced/clusters/:childId')
|
||||
async getActivityClusters(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('type') type: string,
|
||||
@Query('days') days?: string,
|
||||
) {
|
||||
const daysNum = days ? parseInt(days, 10) : 30;
|
||||
|
||||
// Validate activity type
|
||||
if (!Object.values(ActivityType).includes(type as ActivityType)) {
|
||||
throw new BadRequestException('Invalid activity type');
|
||||
}
|
||||
|
||||
try {
|
||||
const clusters = await this.advancedPatternService.clusterActivities(
|
||||
childId,
|
||||
type as ActivityType,
|
||||
daysNum,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: clusters,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
@Get('advanced/correlations/:childId')
|
||||
async getCorrelations(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('days') days?: string,
|
||||
) {
|
||||
const daysNum = days ? parseInt(days, 10) : 14;
|
||||
|
||||
try {
|
||||
const correlations = await this.advancedPatternService.analyzeCorrelations(
|
||||
childId,
|
||||
daysNum,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: correlations,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
@Get('advanced/trends/:childId')
|
||||
async getTrends(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('type') type: string,
|
||||
) {
|
||||
// Validate activity type
|
||||
if (!Object.values(ActivityType).includes(type as ActivityType)) {
|
||||
throw new BadRequestException('Invalid activity type');
|
||||
}
|
||||
|
||||
try {
|
||||
const trends = await this.advancedPatternService.analyzeTrends(
|
||||
childId,
|
||||
type as ActivityType,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: trends,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Growth Analytics Endpoints
|
||||
*/
|
||||
|
||||
@Post('growth/percentile/:childId')
|
||||
async calculateGrowthPercentile(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Body() measurement: {
|
||||
date: string;
|
||||
weight?: number;
|
||||
height?: number;
|
||||
headCircumference?: number;
|
||||
},
|
||||
) {
|
||||
try {
|
||||
const measurementData = {
|
||||
date: new Date(measurement.date),
|
||||
weight: measurement.weight,
|
||||
height: measurement.height,
|
||||
headCircumference: measurement.headCircumference,
|
||||
};
|
||||
|
||||
const percentiles = await this.growthPercentileService.calculateGrowthPercentiles(
|
||||
childId,
|
||||
measurementData,
|
||||
);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: percentiles,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
@Get('growth/analysis/:childId')
|
||||
async analyzeGrowth(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
) {
|
||||
try {
|
||||
const analysis = await this.growthPercentileService.analyzeGrowth(childId);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: analysis,
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Comprehensive Analytics Dashboard Endpoint
|
||||
*/
|
||||
|
||||
@Get('dashboard/:childId')
|
||||
async getAnalyticsDashboard(
|
||||
@CurrentUser() user: any,
|
||||
@Param('childId') childId: string,
|
||||
@Query('days') days?: string,
|
||||
) {
|
||||
const daysNum = days ? parseInt(days, 10) : 7;
|
||||
|
||||
try {
|
||||
// Fetch all analytics in parallel
|
||||
const [
|
||||
patterns,
|
||||
predictions,
|
||||
recentActivities,
|
||||
growthAnalysis,
|
||||
anomalies,
|
||||
] = await Promise.all([
|
||||
this.patternAnalysisService.analyzePatterns(childId, daysNum),
|
||||
this.predictionService.generatePredictions(childId),
|
||||
this.reportService.generateReport(childId,
|
||||
new Date(Date.now() - daysNum * 24 * 60 * 60 * 1000),
|
||||
new Date()
|
||||
),
|
||||
this.growthPercentileService.analyzeGrowth(childId).catch(() => null),
|
||||
this.advancedPatternService.detectAnomalies(childId, daysNum).catch(() => null),
|
||||
]);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
data: {
|
||||
patterns,
|
||||
predictions,
|
||||
recentSummary: recentActivities,
|
||||
growth: growthAnalysis,
|
||||
alerts: anomalies?.alerts || [],
|
||||
generatedAt: new Date(),
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
throw new BadRequestException(error.message);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -7,13 +7,29 @@ import { PatternAnalysisService } from './pattern-analysis.service';
|
||||
import { PredictionService } from './prediction.service';
|
||||
import { ReportService } from './report.service';
|
||||
import { ComparisonService } from './comparison.service';
|
||||
import { AdvancedPatternService } from './advanced-pattern.service';
|
||||
import { GrowthPercentileService } from './growth-percentile.service';
|
||||
import { AnalyticsController } from './analytics.controller';
|
||||
import { InsightsController } from './insights.controller';
|
||||
|
||||
@Module({
|
||||
imports: [TypeOrmModule.forFeature([Activity, Child, FamilyMember])],
|
||||
controllers: [AnalyticsController, InsightsController],
|
||||
providers: [PatternAnalysisService, PredictionService, ReportService, ComparisonService],
|
||||
exports: [PatternAnalysisService, PredictionService, ReportService, ComparisonService],
|
||||
providers: [
|
||||
PatternAnalysisService,
|
||||
PredictionService,
|
||||
ReportService,
|
||||
ComparisonService,
|
||||
AdvancedPatternService,
|
||||
GrowthPercentileService,
|
||||
],
|
||||
exports: [
|
||||
PatternAnalysisService,
|
||||
PredictionService,
|
||||
ReportService,
|
||||
ComparisonService,
|
||||
AdvancedPatternService,
|
||||
GrowthPercentileService,
|
||||
],
|
||||
})
|
||||
export class AnalyticsModule {}
|
||||
|
||||
@@ -0,0 +1,275 @@
|
||||
import { Test, TestingModule } from '@nestjs/testing';
|
||||
import { GrowthPercentileService } from './growth-percentile.service';
|
||||
import { getRepositoryToken } from '@nestjs/typeorm';
|
||||
import { Child } from '../../database/entities/child.entity';
|
||||
import { Activity, ActivityType } from '../../database/entities/activity.entity';
|
||||
import { Repository } from 'typeorm';
|
||||
|
||||
describe('GrowthPercentileService', () => {
|
||||
let service: GrowthPercentileService;
|
||||
let childRepository: Repository<Child>;
|
||||
let activityRepository: Repository<Activity>;
|
||||
|
||||
const mockChild = {
|
||||
id: 'child123',
|
||||
name: 'Test Child',
|
||||
birthDate: new Date('2023-01-01'),
|
||||
gender: 'male',
|
||||
};
|
||||
|
||||
const mockGrowthActivities = [
|
||||
{
|
||||
id: '1',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: new Date('2023-01-01'),
|
||||
endedAt: null,
|
||||
loggedBy: 'user123',
|
||||
metadata: {
|
||||
weight: 3.5, // kg
|
||||
height: 50, // cm
|
||||
headCircumference: 35, // cm
|
||||
},
|
||||
createdAt: new Date('2023-01-01'),
|
||||
updatedAt: new Date('2023-01-01'),
|
||||
},
|
||||
{
|
||||
id: '2',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: new Date('2023-06-01'),
|
||||
endedAt: null,
|
||||
loggedBy: 'user123',
|
||||
metadata: {
|
||||
weight: 7.5,
|
||||
height: 65,
|
||||
headCircumference: 42,
|
||||
},
|
||||
createdAt: new Date('2023-06-01'),
|
||||
updatedAt: new Date('2023-06-01'),
|
||||
},
|
||||
{
|
||||
id: '3',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: new Date('2023-12-01'),
|
||||
endedAt: null,
|
||||
loggedBy: 'user123',
|
||||
metadata: {
|
||||
weight: 10.0,
|
||||
height: 75,
|
||||
headCircumference: 46,
|
||||
},
|
||||
createdAt: new Date('2023-12-01'),
|
||||
updatedAt: new Date('2023-12-01'),
|
||||
},
|
||||
] as unknown as Activity[];
|
||||
|
||||
beforeEach(async () => {
|
||||
const module: TestingModule = await Test.createTestingModule({
|
||||
providers: [
|
||||
GrowthPercentileService,
|
||||
{
|
||||
provide: getRepositoryToken(Child),
|
||||
useValue: {
|
||||
findOne: jest.fn(),
|
||||
find: jest.fn(),
|
||||
},
|
||||
},
|
||||
{
|
||||
provide: getRepositoryToken(Activity),
|
||||
useValue: {
|
||||
find: jest.fn(),
|
||||
findOne: jest.fn(),
|
||||
save: jest.fn(),
|
||||
},
|
||||
},
|
||||
],
|
||||
}).compile();
|
||||
|
||||
service = module.get<GrowthPercentileService>(GrowthPercentileService);
|
||||
childRepository = module.get<Repository<Child>>(getRepositoryToken(Child));
|
||||
activityRepository = module.get<Repository<Activity>>(
|
||||
getRepositoryToken(Activity),
|
||||
);
|
||||
});
|
||||
|
||||
it('should be defined', () => {
|
||||
expect(service).toBeDefined();
|
||||
});
|
||||
|
||||
describe('calculateGrowthPercentiles', () => {
|
||||
it('should calculate percentiles for a male child', async () => {
|
||||
const measurement = {
|
||||
date: new Date('2023-06-01'),
|
||||
weight: 7.5,
|
||||
height: 65,
|
||||
headCircumference: 42,
|
||||
};
|
||||
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'save').mockResolvedValue({
|
||||
id: 'new-measurement',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: measurement.date,
|
||||
endedAt: null,
|
||||
loggedBy: 'user123',
|
||||
metadata: measurement,
|
||||
createdAt: measurement.date,
|
||||
updatedAt: measurement.date,
|
||||
} as unknown as Activity);
|
||||
|
||||
const result = await service.calculateGrowthPercentiles('child123', measurement);
|
||||
|
||||
expect(result).toHaveProperty('weight');
|
||||
expect(result).toHaveProperty('height');
|
||||
expect(result).toHaveProperty('headCircumference');
|
||||
|
||||
// Check weight percentile
|
||||
if (result.weight) {
|
||||
expect(result.weight).toHaveProperty('value');
|
||||
expect(result.weight).toHaveProperty('percentile');
|
||||
expect(result.weight).toHaveProperty('zScore');
|
||||
expect(result.weight.percentile).toBeGreaterThanOrEqual(0);
|
||||
expect(result.weight.percentile).toBeLessThanOrEqual(100);
|
||||
}
|
||||
});
|
||||
|
||||
it('should handle partial measurements', async () => {
|
||||
const measurement = {
|
||||
date: new Date('2023-06-01'),
|
||||
weight: 7.5,
|
||||
// No height or head circumference
|
||||
};
|
||||
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'save').mockResolvedValue({
|
||||
id: 'new-measurement',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: measurement.date,
|
||||
metadata: measurement,
|
||||
} as unknown as Activity);
|
||||
|
||||
const result = await service.calculateGrowthPercentiles('child123', measurement);
|
||||
|
||||
expect(result.weight).toBeDefined();
|
||||
expect(result.height).toBeUndefined();
|
||||
expect(result.headCircumference).toBeUndefined();
|
||||
});
|
||||
|
||||
it('should throw error if child not found', async () => {
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(null);
|
||||
|
||||
await expect(
|
||||
service.calculateGrowthPercentiles('invalid', {
|
||||
date: new Date(),
|
||||
weight: 5,
|
||||
}),
|
||||
).rejects.toThrow('Child not found');
|
||||
});
|
||||
});
|
||||
|
||||
describe('analyzeGrowth', () => {
|
||||
it('should analyze growth trends and velocity', async () => {
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'find').mockResolvedValue(mockGrowthActivities);
|
||||
|
||||
const result = await service.analyzeGrowth('child123');
|
||||
|
||||
expect(result).toHaveProperty('currentPercentiles');
|
||||
expect(result).toHaveProperty('growthVelocity');
|
||||
expect(result).toHaveProperty('growthCurve');
|
||||
expect(result).toHaveProperty('projections');
|
||||
expect(result).toHaveProperty('recommendations');
|
||||
expect(result).toHaveProperty('alerts');
|
||||
});
|
||||
|
||||
it('should detect growth alerts for rapid weight gain', async () => {
|
||||
const rapidGrowthActivities = [
|
||||
...mockGrowthActivities,
|
||||
{
|
||||
id: '4',
|
||||
childId: 'child123',
|
||||
type: ActivityType.GROWTH,
|
||||
startedAt: new Date('2024-01-01'),
|
||||
endedAt: null,
|
||||
loggedBy: 'user123',
|
||||
metadata: {
|
||||
weight: 15.0, // Rapid weight gain
|
||||
height: 78,
|
||||
headCircumference: 47,
|
||||
},
|
||||
createdAt: new Date('2024-01-01'),
|
||||
updatedAt: new Date('2024-01-01'),
|
||||
},
|
||||
] as unknown as Activity[];
|
||||
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'find').mockResolvedValue(rapidGrowthActivities);
|
||||
|
||||
const result = await service.analyzeGrowth('child123');
|
||||
|
||||
expect(result.alerts).toBeDefined();
|
||||
expect(Array.isArray(result.alerts)).toBe(true);
|
||||
|
||||
// Should have at least one alert
|
||||
if (result.alerts.length > 0) {
|
||||
expect(result.alerts[0]).toHaveProperty('type');
|
||||
expect(result.alerts[0]).toHaveProperty('severity');
|
||||
expect(result.alerts[0]).toHaveProperty('message');
|
||||
}
|
||||
});
|
||||
|
||||
it('should throw error for no measurements', async () => {
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'find').mockResolvedValue([]);
|
||||
|
||||
await expect(service.analyzeGrowth('child123'))
|
||||
.rejects.toThrow('No growth measurements found');
|
||||
});
|
||||
|
||||
it('should calculate correct growth velocity', async () => {
|
||||
const twoMeasurements = mockGrowthActivities.slice(0, 2);
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(mockChild as Child);
|
||||
jest.spyOn(activityRepository, 'find').mockResolvedValue(twoMeasurements);
|
||||
|
||||
const result = await service.analyzeGrowth('child123');
|
||||
|
||||
expect(result.growthVelocity).toBeDefined();
|
||||
expect(result.growthVelocity).toHaveProperty('weightVelocity');
|
||||
expect(result.growthVelocity).toHaveProperty('heightVelocity');
|
||||
|
||||
// Weight velocity should be positive (gaining weight)
|
||||
if (result.growthVelocity.weightVelocity) {
|
||||
expect(result.growthVelocity.weightVelocity.value).toBeGreaterThan(0);
|
||||
}
|
||||
|
||||
// Height velocity should be positive (growing taller)
|
||||
if (result.growthVelocity.heightVelocity) {
|
||||
expect(result.growthVelocity.heightVelocity.value).toBeGreaterThan(0);
|
||||
}
|
||||
});
|
||||
|
||||
it('should provide age-appropriate recommendations', async () => {
|
||||
// Test for newborn (0-3 months)
|
||||
const newbornChild = { ...mockChild, birthDate: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000) };
|
||||
jest.spyOn(childRepository, 'findOne').mockResolvedValue(newbornChild as Child);
|
||||
jest.spyOn(activityRepository, 'find').mockResolvedValue([
|
||||
{
|
||||
...mockGrowthActivities[0],
|
||||
startedAt: new Date(),
|
||||
},
|
||||
] as Activity[]);
|
||||
|
||||
const result = await service.analyzeGrowth('child123');
|
||||
|
||||
expect(result.recommendations).toBeDefined();
|
||||
expect(Array.isArray(result.recommendations)).toBe(true);
|
||||
expect(result.recommendations.length).toBeGreaterThan(0);
|
||||
});
|
||||
});
|
||||
|
||||
|
||||
});
|
||||
@@ -0,0 +1,870 @@
|
||||
import { Injectable, Logger } from '@nestjs/common';
|
||||
import { InjectRepository } from '@nestjs/typeorm';
|
||||
import { Repository, Between } from 'typeorm';
|
||||
import { Activity, ActivityType } from '../../database/entities/activity.entity';
|
||||
import { Child } from '../../database/entities/child.entity';
|
||||
|
||||
/**
|
||||
* Growth Percentile Service
|
||||
*
|
||||
* Implements WHO and CDC growth charts for children 0-6 years
|
||||
* Calculates percentiles, z-scores, and growth velocity
|
||||
* Detects growth concerns and provides recommendations
|
||||
*/
|
||||
|
||||
export interface GrowthMeasurement {
|
||||
date: Date;
|
||||
weight?: number; // kg
|
||||
height?: number; // cm
|
||||
headCircumference?: number; // cm
|
||||
}
|
||||
|
||||
export interface GrowthPercentile {
|
||||
weight?: PercentileData;
|
||||
height?: PercentileData;
|
||||
headCircumference?: PercentileData;
|
||||
bmi?: PercentileData;
|
||||
weightForLength?: PercentileData;
|
||||
}
|
||||
|
||||
export interface PercentileData {
|
||||
value: number;
|
||||
percentile: number;
|
||||
zScore: number;
|
||||
interpretation: 'underweight' | 'normal' | 'overweight' | 'obese' | 'short' | 'tall';
|
||||
ageInMonths: number;
|
||||
}
|
||||
|
||||
export interface GrowthVelocity {
|
||||
weightVelocity?: VelocityData;
|
||||
heightVelocity?: VelocityData;
|
||||
interpretation: string;
|
||||
concerns: string[];
|
||||
}
|
||||
|
||||
export interface VelocityData {
|
||||
value: number; // kg/month or cm/month
|
||||
percentile: number;
|
||||
isNormal: boolean;
|
||||
trend: 'accelerating' | 'steady' | 'decelerating';
|
||||
}
|
||||
|
||||
export interface GrowthAnalysis {
|
||||
currentPercentiles: GrowthPercentile;
|
||||
growthVelocity: GrowthVelocity;
|
||||
growthCurve: GrowthCurveData;
|
||||
projections: GrowthProjection;
|
||||
recommendations: string[];
|
||||
alerts: GrowthAlert[];
|
||||
}
|
||||
|
||||
export interface GrowthCurveData {
|
||||
measurements: GrowthMeasurement[];
|
||||
percentileCurves: {
|
||||
p3: number[];
|
||||
p15: number[];
|
||||
p50: number[];
|
||||
p85: number[];
|
||||
p97: number[];
|
||||
};
|
||||
childCurve: number[];
|
||||
}
|
||||
|
||||
export interface GrowthProjection {
|
||||
projectedWeight: { value: number; date: Date; confidence: number };
|
||||
projectedHeight: { value: number; date: Date; confidence: number };
|
||||
expectedAdultHeight?: number; // Using mid-parental height method
|
||||
}
|
||||
|
||||
export interface GrowthAlert {
|
||||
type: 'crossing_percentiles' | 'stunting' | 'wasting' | 'obesity_risk' | 'failure_to_thrive';
|
||||
severity: 'info' | 'warning' | 'critical';
|
||||
message: string;
|
||||
recommendation: string;
|
||||
}
|
||||
|
||||
// WHO Growth Standard Data (simplified - in production, use complete tables)
|
||||
const WHO_WEIGHT_FOR_AGE_BOYS = {
|
||||
// Age in months -> [P3, P15, P50, P85, P97] in kg
|
||||
0: [2.5, 2.9, 3.3, 3.9, 4.4],
|
||||
1: [3.4, 3.9, 4.5, 5.1, 5.8],
|
||||
2: [4.3, 4.9, 5.6, 6.3, 7.1],
|
||||
3: [5.0, 5.7, 6.4, 7.2, 8.0],
|
||||
6: [6.4, 7.1, 7.9, 8.8, 9.8],
|
||||
9: [7.2, 8.0, 8.9, 9.9, 11.0],
|
||||
12: [7.7, 8.5, 9.6, 10.8, 12.0],
|
||||
18: [8.8, 9.8, 11.0, 12.5, 13.7],
|
||||
24: [9.7, 10.8, 12.2, 13.6, 15.3],
|
||||
36: [11.3, 12.7, 14.3, 16.2, 18.3],
|
||||
48: [12.7, 14.3, 16.3, 18.5, 21.2],
|
||||
60: [14.1, 15.9, 18.3, 21.0, 24.2],
|
||||
};
|
||||
|
||||
const WHO_WEIGHT_FOR_AGE_GIRLS = {
|
||||
0: [2.4, 2.8, 3.2, 3.7, 4.2],
|
||||
1: [3.2, 3.6, 4.2, 4.8, 5.5],
|
||||
2: [3.9, 4.5, 5.1, 5.8, 6.6],
|
||||
3: [4.5, 5.2, 5.8, 6.6, 7.5],
|
||||
6: [5.7, 6.4, 7.3, 8.2, 9.3],
|
||||
9: [6.5, 7.3, 8.2, 9.3, 10.5],
|
||||
12: [7.0, 7.9, 8.9, 10.1, 11.5],
|
||||
18: [8.2, 9.2, 10.4, 11.8, 13.5],
|
||||
24: [9.0, 10.2, 11.5, 13.0, 15.0],
|
||||
36: [10.8, 12.1, 13.9, 15.8, 18.1],
|
||||
48: [12.3, 13.9, 15.9, 18.5, 21.5],
|
||||
60: [13.7, 15.8, 18.2, 21.2, 24.9],
|
||||
};
|
||||
|
||||
const WHO_HEIGHT_FOR_AGE_BOYS = {
|
||||
// Age in months -> [P3, P15, P50, P85, P97] in cm
|
||||
0: [46.1, 48.0, 49.9, 51.8, 53.7],
|
||||
1: [50.8, 52.8, 54.7, 56.7, 58.6],
|
||||
2: [54.4, 56.4, 58.4, 60.4, 62.4],
|
||||
3: [57.3, 59.4, 61.4, 63.5, 65.5],
|
||||
6: [63.3, 65.5, 67.6, 69.8, 71.9],
|
||||
9: [68.0, 70.3, 72.0, 74.5, 76.5],
|
||||
12: [71.0, 73.4, 75.7, 78.1, 80.5],
|
||||
18: [76.9, 79.6, 82.3, 85.0, 87.8],
|
||||
24: [81.7, 84.8, 87.8, 90.9, 94.0],
|
||||
36: [88.7, 92.4, 96.1, 99.8, 103.5],
|
||||
48: [94.9, 99.1, 103.3, 107.5, 111.7],
|
||||
60: [100.7, 105.3, 110.0, 114.6, 119.2],
|
||||
};
|
||||
|
||||
const WHO_HEIGHT_FOR_AGE_GIRLS = {
|
||||
0: [45.4, 47.3, 49.1, 51.0, 52.9],
|
||||
1: [49.8, 51.7, 53.7, 55.6, 57.6],
|
||||
2: [53.0, 55.0, 57.1, 59.1, 61.1],
|
||||
3: [55.6, 57.7, 59.8, 61.9, 64.0],
|
||||
6: [61.2, 63.5, 65.7, 68.0, 70.3],
|
||||
9: [65.3, 67.7, 70.1, 72.6, 75.0],
|
||||
12: [68.9, 71.4, 74.0, 76.6, 79.2],
|
||||
18: [74.9, 77.8, 80.7, 83.6, 86.5],
|
||||
24: [80.0, 83.2, 86.4, 89.6, 92.9],
|
||||
36: [87.4, 91.2, 95.1, 98.9, 102.7],
|
||||
48: [94.1, 98.4, 102.7, 107.0, 111.3],
|
||||
60: [99.9, 104.7, 109.4, 114.2, 118.9],
|
||||
};
|
||||
|
||||
@Injectable()
|
||||
export class GrowthPercentileService {
|
||||
private readonly logger = new Logger('GrowthPercentileService');
|
||||
|
||||
constructor(
|
||||
@InjectRepository(Activity)
|
||||
private activityRepository: Repository<Activity>,
|
||||
@InjectRepository(Child)
|
||||
private childRepository: Repository<Child>,
|
||||
) {}
|
||||
|
||||
/**
|
||||
* Calculate growth percentiles for a child
|
||||
*/
|
||||
async calculateGrowthPercentiles(
|
||||
childId: string,
|
||||
measurement: GrowthMeasurement,
|
||||
): Promise<GrowthPercentile> {
|
||||
const child = await this.childRepository.findOne({ where: { id: childId } });
|
||||
if (!child) {
|
||||
throw new Error('Child not found');
|
||||
}
|
||||
|
||||
const ageInMonths = this.calculateAgeInMonths(child.birthDate, measurement.date);
|
||||
const gender = child.gender as 'male' | 'female';
|
||||
|
||||
const result: GrowthPercentile = {};
|
||||
|
||||
if (measurement.weight !== undefined) {
|
||||
result.weight = this.calculateWeightPercentile(
|
||||
measurement.weight,
|
||||
ageInMonths,
|
||||
gender,
|
||||
);
|
||||
}
|
||||
|
||||
if (measurement.height !== undefined) {
|
||||
result.height = this.calculateHeightPercentile(
|
||||
measurement.height,
|
||||
ageInMonths,
|
||||
gender,
|
||||
);
|
||||
}
|
||||
|
||||
if (measurement.weight && measurement.height) {
|
||||
result.bmi = this.calculateBMIPercentile(
|
||||
measurement.weight,
|
||||
measurement.height,
|
||||
ageInMonths,
|
||||
gender,
|
||||
);
|
||||
|
||||
if (ageInMonths < 24) {
|
||||
result.weightForLength = this.calculateWeightForLength(
|
||||
measurement.weight,
|
||||
measurement.height,
|
||||
gender,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (measurement.headCircumference !== undefined && ageInMonths < 36) {
|
||||
result.headCircumference = this.calculateHeadCircumferencePercentile(
|
||||
measurement.headCircumference,
|
||||
ageInMonths,
|
||||
gender,
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* Analyze growth patterns and detect concerns
|
||||
*/
|
||||
async analyzeGrowth(childId: string): Promise<GrowthAnalysis> {
|
||||
const child = await this.childRepository.findOne({ where: { id: childId } });
|
||||
if (!child) {
|
||||
throw new Error('Child not found');
|
||||
}
|
||||
|
||||
// Get growth measurements from activities
|
||||
const measurements = await this.getGrowthMeasurements(childId);
|
||||
|
||||
if (measurements.length === 0) {
|
||||
throw new Error('No growth measurements found');
|
||||
}
|
||||
|
||||
// Calculate current percentiles
|
||||
const latestMeasurement = measurements[measurements.length - 1];
|
||||
const currentPercentiles = await this.calculateGrowthPercentiles(
|
||||
childId,
|
||||
latestMeasurement,
|
||||
);
|
||||
|
||||
// Calculate growth velocity
|
||||
const growthVelocity = this.calculateGrowthVelocity(measurements, child);
|
||||
|
||||
// Build growth curves
|
||||
const growthCurve = this.buildGrowthCurve(measurements, child);
|
||||
|
||||
// Generate projections
|
||||
const projections = this.generateGrowthProjections(
|
||||
measurements,
|
||||
child,
|
||||
growthVelocity,
|
||||
);
|
||||
|
||||
// Detect alerts and generate recommendations
|
||||
const alerts = this.detectGrowthAlerts(
|
||||
currentPercentiles,
|
||||
growthVelocity,
|
||||
measurements,
|
||||
child,
|
||||
);
|
||||
|
||||
const recommendations = this.generateGrowthRecommendations(
|
||||
currentPercentiles,
|
||||
growthVelocity,
|
||||
alerts,
|
||||
);
|
||||
|
||||
return {
|
||||
currentPercentiles,
|
||||
growthVelocity,
|
||||
growthCurve,
|
||||
projections,
|
||||
recommendations,
|
||||
alerts,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate weight percentile
|
||||
*/
|
||||
private calculateWeightPercentile(
|
||||
weight: number,
|
||||
ageInMonths: number,
|
||||
gender: 'male' | 'female',
|
||||
): PercentileData {
|
||||
const growthData = gender === 'male' ? WHO_WEIGHT_FOR_AGE_BOYS : WHO_WEIGHT_FOR_AGE_GIRLS;
|
||||
const ageKey = this.getNearestAgeKey(ageInMonths, growthData);
|
||||
const percentiles = growthData[ageKey];
|
||||
|
||||
const percentile = this.calculatePercentileFromValue(weight, percentiles);
|
||||
const zScore = this.calculateZScore(weight, percentiles);
|
||||
|
||||
let interpretation: PercentileData['interpretation'] = 'normal';
|
||||
if (percentile < 3) interpretation = 'underweight';
|
||||
else if (percentile > 97) interpretation = 'overweight';
|
||||
else if (percentile > 95 && ageInMonths > 24) interpretation = 'obese';
|
||||
|
||||
return {
|
||||
value: weight,
|
||||
percentile,
|
||||
zScore,
|
||||
interpretation,
|
||||
ageInMonths,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate height percentile
|
||||
*/
|
||||
private calculateHeightPercentile(
|
||||
height: number,
|
||||
ageInMonths: number,
|
||||
gender: 'male' | 'female',
|
||||
): PercentileData {
|
||||
const growthData = gender === 'male' ? WHO_HEIGHT_FOR_AGE_BOYS : WHO_HEIGHT_FOR_AGE_GIRLS;
|
||||
const ageKey = this.getNearestAgeKey(ageInMonths, growthData);
|
||||
const percentiles = growthData[ageKey];
|
||||
|
||||
const percentile = this.calculatePercentileFromValue(height, percentiles);
|
||||
const zScore = this.calculateZScore(height, percentiles);
|
||||
|
||||
let interpretation: PercentileData['interpretation'] = 'normal';
|
||||
if (percentile < 3) interpretation = 'short';
|
||||
else if (percentile > 97) interpretation = 'tall';
|
||||
|
||||
return {
|
||||
value: height,
|
||||
percentile,
|
||||
zScore,
|
||||
interpretation,
|
||||
ageInMonths,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate BMI percentile
|
||||
*/
|
||||
private calculateBMIPercentile(
|
||||
weight: number,
|
||||
height: number,
|
||||
ageInMonths: number,
|
||||
gender: 'male' | 'female',
|
||||
): PercentileData {
|
||||
const bmi = weight / Math.pow(height / 100, 2);
|
||||
|
||||
// Simplified BMI percentile calculation
|
||||
// In production, use CDC BMI-for-age charts
|
||||
let percentile = 50;
|
||||
let interpretation: PercentileData['interpretation'] = 'normal';
|
||||
|
||||
if (ageInMonths >= 24) {
|
||||
if (bmi < 14) {
|
||||
percentile = 5;
|
||||
interpretation = 'underweight';
|
||||
} else if (bmi < 16) {
|
||||
percentile = 25;
|
||||
interpretation = 'normal';
|
||||
} else if (bmi < 18) {
|
||||
percentile = 50;
|
||||
interpretation = 'normal';
|
||||
} else if (bmi < 20) {
|
||||
percentile = 75;
|
||||
interpretation = 'normal';
|
||||
} else if (bmi < 23) {
|
||||
percentile = 90;
|
||||
interpretation = 'overweight';
|
||||
} else {
|
||||
percentile = 97;
|
||||
interpretation = 'obese';
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
value: bmi,
|
||||
percentile,
|
||||
zScore: this.percentileToZScore(percentile),
|
||||
interpretation,
|
||||
ageInMonths,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate weight-for-length percentile (for infants < 24 months)
|
||||
*/
|
||||
private calculateWeightForLength(
|
||||
weight: number,
|
||||
length: number,
|
||||
gender: 'male' | 'female',
|
||||
): PercentileData {
|
||||
// Simplified calculation - in production, use WHO weight-for-length tables
|
||||
const ratio = weight / (length / 100);
|
||||
let percentile = 50;
|
||||
let interpretation: PercentileData['interpretation'] = 'normal';
|
||||
|
||||
if (ratio < 10) {
|
||||
percentile = 5;
|
||||
interpretation = 'underweight';
|
||||
} else if (ratio > 18) {
|
||||
percentile = 95;
|
||||
interpretation = 'overweight';
|
||||
}
|
||||
|
||||
return {
|
||||
value: ratio,
|
||||
percentile,
|
||||
zScore: this.percentileToZScore(percentile),
|
||||
interpretation,
|
||||
ageInMonths: 0, // Not age-dependent
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate head circumference percentile
|
||||
*/
|
||||
private calculateHeadCircumferencePercentile(
|
||||
circumference: number,
|
||||
ageInMonths: number,
|
||||
gender: 'male' | 'female',
|
||||
): PercentileData {
|
||||
// Simplified - in production, use WHO head circumference charts
|
||||
const expectedCircumference = 35 + ageInMonths * 0.5; // Very simplified
|
||||
const deviation = circumference - expectedCircumference;
|
||||
const percentile = this.normalCDF(deviation / 2) * 100;
|
||||
|
||||
let interpretation: PercentileData['interpretation'] = 'normal';
|
||||
if (percentile < 3 || percentile > 97) {
|
||||
interpretation = percentile < 3 ? 'short' : 'tall'; // Using as proxy
|
||||
}
|
||||
|
||||
return {
|
||||
value: circumference,
|
||||
percentile,
|
||||
zScore: this.percentileToZScore(percentile),
|
||||
interpretation,
|
||||
ageInMonths,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate growth velocity
|
||||
*/
|
||||
private calculateGrowthVelocity(
|
||||
measurements: GrowthMeasurement[],
|
||||
child: Child,
|
||||
): GrowthVelocity {
|
||||
if (measurements.length < 2) {
|
||||
return {
|
||||
interpretation: 'Insufficient data for velocity calculation',
|
||||
concerns: [],
|
||||
};
|
||||
}
|
||||
|
||||
const recent = measurements.slice(-3); // Last 3 measurements
|
||||
const velocity: GrowthVelocity = {
|
||||
interpretation: '',
|
||||
concerns: [],
|
||||
};
|
||||
|
||||
// Calculate weight velocity
|
||||
const weightMeasurements = recent.filter((m) => m.weight !== undefined);
|
||||
if (weightMeasurements.length >= 2) {
|
||||
const first = weightMeasurements[0];
|
||||
const last = weightMeasurements[weightMeasurements.length - 1];
|
||||
const monthsDiff = this.monthsDifference(first.date, last.date);
|
||||
|
||||
if (monthsDiff > 0) {
|
||||
const weightGain = (last.weight! - first.weight!) / monthsDiff;
|
||||
const expectedGain = this.getExpectedWeightGain(child, first.date);
|
||||
|
||||
velocity.weightVelocity = {
|
||||
value: weightGain,
|
||||
percentile: (weightGain / expectedGain) * 50, // Simplified
|
||||
isNormal: Math.abs(weightGain - expectedGain) / expectedGain < 0.3,
|
||||
trend:
|
||||
weightGain > expectedGain * 1.2 ? 'accelerating' :
|
||||
weightGain < expectedGain * 0.8 ? 'decelerating' :
|
||||
'steady',
|
||||
};
|
||||
|
||||
if (!velocity.weightVelocity.isNormal) {
|
||||
velocity.concerns.push(
|
||||
weightGain < expectedGain * 0.5
|
||||
? 'Poor weight gain detected'
|
||||
: weightGain > expectedGain * 1.5
|
||||
? 'Rapid weight gain detected'
|
||||
: 'Weight gain outside normal range'
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate height velocity
|
||||
const heightMeasurements = recent.filter((m) => m.height !== undefined);
|
||||
if (heightMeasurements.length >= 2) {
|
||||
const first = heightMeasurements[0];
|
||||
const last = heightMeasurements[heightMeasurements.length - 1];
|
||||
const monthsDiff = this.monthsDifference(first.date, last.date);
|
||||
|
||||
if (monthsDiff > 0) {
|
||||
const heightGain = (last.height! - first.height!) / monthsDiff;
|
||||
const expectedGain = this.getExpectedHeightGain(child, first.date);
|
||||
|
||||
velocity.heightVelocity = {
|
||||
value: heightGain,
|
||||
percentile: (heightGain / expectedGain) * 50, // Simplified
|
||||
isNormal: Math.abs(heightGain - expectedGain) / expectedGain < 0.3,
|
||||
trend:
|
||||
heightGain > expectedGain * 1.2 ? 'accelerating' :
|
||||
heightGain < expectedGain * 0.8 ? 'decelerating' :
|
||||
'steady',
|
||||
};
|
||||
|
||||
if (!velocity.heightVelocity.isNormal) {
|
||||
velocity.concerns.push(
|
||||
heightGain < expectedGain * 0.5
|
||||
? 'Poor linear growth detected'
|
||||
: 'Height velocity outside normal range'
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Set interpretation
|
||||
if (velocity.weightVelocity && velocity.heightVelocity) {
|
||||
if (velocity.weightVelocity.isNormal && velocity.heightVelocity.isNormal) {
|
||||
velocity.interpretation = 'Growth velocity is within normal range';
|
||||
} else {
|
||||
velocity.interpretation = 'Growth velocity shows concerning patterns';
|
||||
}
|
||||
} else {
|
||||
velocity.interpretation = 'Partial growth velocity data available';
|
||||
}
|
||||
|
||||
return velocity;
|
||||
}
|
||||
|
||||
/**
|
||||
* Build growth curve data for visualization
|
||||
*/
|
||||
private buildGrowthCurve(
|
||||
measurements: GrowthMeasurement[],
|
||||
child: Child,
|
||||
): GrowthCurveData {
|
||||
const gender = child.gender as 'male' | 'female';
|
||||
const weightData = gender === 'male' ? WHO_WEIGHT_FOR_AGE_BOYS : WHO_WEIGHT_FOR_AGE_GIRLS;
|
||||
|
||||
// Extract percentile curves
|
||||
const ages = Object.keys(weightData).map(Number).sort((a, b) => a - b);
|
||||
const percentileCurves = {
|
||||
p3: ages.map(age => weightData[age][0]),
|
||||
p15: ages.map(age => weightData[age][1]),
|
||||
p50: ages.map(age => weightData[age][2]),
|
||||
p85: ages.map(age => weightData[age][3]),
|
||||
p97: ages.map(age => weightData[age][4]),
|
||||
};
|
||||
|
||||
// Build child's curve
|
||||
const childCurve = measurements
|
||||
.filter(m => m.weight !== undefined)
|
||||
.map(m => m.weight!);
|
||||
|
||||
return {
|
||||
measurements,
|
||||
percentileCurves,
|
||||
childCurve,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate growth projections
|
||||
*/
|
||||
private generateGrowthProjections(
|
||||
measurements: GrowthMeasurement[],
|
||||
child: Child,
|
||||
velocity: GrowthVelocity,
|
||||
): GrowthProjection {
|
||||
const lastMeasurement = measurements[measurements.length - 1];
|
||||
const projectionDate = new Date();
|
||||
projectionDate.setMonth(projectionDate.getMonth() + 3); // 3 months ahead
|
||||
|
||||
// Project weight
|
||||
const projectedWeight = velocity.weightVelocity
|
||||
? {
|
||||
value: lastMeasurement.weight! + velocity.weightVelocity.value * 3,
|
||||
date: projectionDate,
|
||||
confidence: velocity.weightVelocity.isNormal ? 0.8 : 0.5,
|
||||
}
|
||||
: {
|
||||
value: lastMeasurement.weight || 0,
|
||||
date: projectionDate,
|
||||
confidence: 0.3,
|
||||
};
|
||||
|
||||
// Project height
|
||||
const projectedHeight = velocity.heightVelocity
|
||||
? {
|
||||
value: lastMeasurement.height! + velocity.heightVelocity.value * 3,
|
||||
date: projectionDate,
|
||||
confidence: velocity.heightVelocity.isNormal ? 0.8 : 0.5,
|
||||
}
|
||||
: {
|
||||
value: lastMeasurement.height || 0,
|
||||
date: projectionDate,
|
||||
confidence: 0.3,
|
||||
};
|
||||
|
||||
return {
|
||||
projectedWeight,
|
||||
projectedHeight,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Detect growth alerts
|
||||
*/
|
||||
private detectGrowthAlerts(
|
||||
percentiles: GrowthPercentile,
|
||||
velocity: GrowthVelocity,
|
||||
measurements: GrowthMeasurement[],
|
||||
child: Child,
|
||||
): GrowthAlert[] {
|
||||
const alerts: GrowthAlert[] = [];
|
||||
|
||||
// Check for crossing percentiles
|
||||
if (measurements.length >= 3) {
|
||||
const percentileHistory = measurements.slice(-3).map((m) => {
|
||||
if (m.weight) {
|
||||
const ageInMonths = this.calculateAgeInMonths(child.birthDate, m.date);
|
||||
return this.calculateWeightPercentile(
|
||||
m.weight,
|
||||
ageInMonths,
|
||||
child.gender as 'male' | 'female',
|
||||
).percentile;
|
||||
}
|
||||
return null;
|
||||
}).filter((p) => p !== null) as number[];
|
||||
|
||||
if (percentileHistory.length >= 2) {
|
||||
const change = Math.abs(percentileHistory[percentileHistory.length - 1] - percentileHistory[0]);
|
||||
if (change > 25) {
|
||||
alerts.push({
|
||||
type: 'crossing_percentiles',
|
||||
severity: change > 50 ? 'critical' : 'warning',
|
||||
message: `Child has crossed ${Math.round(change)} percentile lines`,
|
||||
recommendation: 'Consult pediatrician about growth pattern changes',
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Check for stunting (low height-for-age)
|
||||
if (percentiles.height && percentiles.height.percentile < 3) {
|
||||
alerts.push({
|
||||
type: 'stunting',
|
||||
severity: percentiles.height.percentile < 1 ? 'critical' : 'warning',
|
||||
message: 'Height is below the 3rd percentile for age',
|
||||
recommendation: 'Evaluate nutrition and consider pediatric endocrinology referral',
|
||||
});
|
||||
}
|
||||
|
||||
// Check for wasting (low weight-for-height)
|
||||
if (percentiles.weightForLength && percentiles.weightForLength.percentile < 3) {
|
||||
alerts.push({
|
||||
type: 'wasting',
|
||||
severity: 'critical',
|
||||
message: 'Weight-for-length is below the 3rd percentile',
|
||||
recommendation: 'Urgent nutritional assessment needed',
|
||||
});
|
||||
}
|
||||
|
||||
// Check for obesity risk
|
||||
if (percentiles.bmi && percentiles.bmi.percentile > 95) {
|
||||
alerts.push({
|
||||
type: 'obesity_risk',
|
||||
severity: percentiles.bmi.percentile > 99 ? 'warning' : 'info',
|
||||
message: 'BMI is above the 95th percentile for age',
|
||||
recommendation: 'Consider lifestyle modifications and dietary counseling',
|
||||
});
|
||||
}
|
||||
|
||||
// Check for failure to thrive
|
||||
if (velocity.concerns.includes('Poor weight gain detected')) {
|
||||
alerts.push({
|
||||
type: 'failure_to_thrive',
|
||||
severity: 'critical',
|
||||
message: 'Poor weight gain velocity detected',
|
||||
recommendation: 'Comprehensive evaluation for failure to thrive indicated',
|
||||
});
|
||||
}
|
||||
|
||||
return alerts;
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate growth recommendations
|
||||
*/
|
||||
private generateGrowthRecommendations(
|
||||
percentiles: GrowthPercentile,
|
||||
velocity: GrowthVelocity,
|
||||
alerts: GrowthAlert[],
|
||||
): string[] {
|
||||
const recommendations: string[] = [];
|
||||
|
||||
// General growth tracking
|
||||
recommendations.push('Continue regular growth monitoring at pediatric visits');
|
||||
|
||||
// Weight-specific recommendations
|
||||
if (percentiles.weight) {
|
||||
if (percentiles.weight.percentile < 10) {
|
||||
recommendations.push('Ensure adequate caloric intake for age');
|
||||
recommendations.push('Consider nutritional supplementation if indicated');
|
||||
} else if (percentiles.weight.percentile > 90) {
|
||||
recommendations.push('Focus on healthy eating habits and portion control');
|
||||
recommendations.push('Encourage age-appropriate physical activity');
|
||||
}
|
||||
}
|
||||
|
||||
// Velocity-specific recommendations
|
||||
if (velocity.weightVelocity && !velocity.weightVelocity.isNormal) {
|
||||
if (velocity.weightVelocity.trend === 'decelerating') {
|
||||
recommendations.push('Monitor feeding patterns and appetite closely');
|
||||
recommendations.push('Rule out underlying medical conditions affecting growth');
|
||||
} else if (velocity.weightVelocity.trend === 'accelerating') {
|
||||
recommendations.push('Evaluate for overfeeding or excessive weight gain');
|
||||
}
|
||||
}
|
||||
|
||||
// Alert-specific recommendations
|
||||
if (alerts.some(a => a.severity === 'critical')) {
|
||||
recommendations.unshift('URGENT: Schedule pediatric evaluation as soon as possible');
|
||||
}
|
||||
|
||||
// Add age-specific recommendations
|
||||
const ageInMonths = this.calculateAgeInMonths(
|
||||
new Date(), // Assuming current age
|
||||
new Date(),
|
||||
);
|
||||
|
||||
if (ageInMonths < 6) {
|
||||
recommendations.push('Ensure appropriate feeding frequency (8-12 times/day for breastfed infants)');
|
||||
} else if (ageInMonths < 12) {
|
||||
recommendations.push('Begin introducing appropriate solid foods if not already started');
|
||||
} else if (ageInMonths < 24) {
|
||||
recommendations.push('Transition to family foods with appropriate texture modifications');
|
||||
}
|
||||
|
||||
return recommendations;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get growth measurements from activities
|
||||
*/
|
||||
private async getGrowthMeasurements(childId: string): Promise<GrowthMeasurement[]> {
|
||||
const growthActivities = await this.activityRepository.find({
|
||||
where: {
|
||||
childId,
|
||||
type: ActivityType.GROWTH,
|
||||
},
|
||||
order: { startedAt: 'ASC' },
|
||||
});
|
||||
|
||||
return growthActivities
|
||||
.filter((a) => a.metadata)
|
||||
.map((a) => ({
|
||||
date: a.startedAt,
|
||||
weight: a.metadata.weight,
|
||||
height: a.metadata.height,
|
||||
headCircumference: a.metadata.headCircumference,
|
||||
}));
|
||||
}
|
||||
|
||||
// Utility methods
|
||||
|
||||
private calculateAgeInMonths(birthDate: Date, currentDate: Date = new Date()): number {
|
||||
const months =
|
||||
(currentDate.getFullYear() - birthDate.getFullYear()) * 12 +
|
||||
(currentDate.getMonth() - birthDate.getMonth());
|
||||
return Math.max(0, months);
|
||||
}
|
||||
|
||||
private monthsDifference(date1: Date, date2: Date): number {
|
||||
return Math.abs(
|
||||
(date2.getFullYear() - date1.getFullYear()) * 12 +
|
||||
(date2.getMonth() - date1.getMonth())
|
||||
);
|
||||
}
|
||||
|
||||
private getNearestAgeKey(ageInMonths: number, data: any): number {
|
||||
const ages = Object.keys(data).map(Number);
|
||||
return ages.reduce((prev, curr) =>
|
||||
Math.abs(curr - ageInMonths) < Math.abs(prev - ageInMonths) ? curr : prev
|
||||
);
|
||||
}
|
||||
|
||||
private calculatePercentileFromValue(value: number, percentiles: number[]): number {
|
||||
// percentiles = [P3, P15, P50, P85, P97]
|
||||
if (value <= percentiles[0]) return 3;
|
||||
if (value <= percentiles[1]) return this.interpolate(value, percentiles[0], percentiles[1], 3, 15);
|
||||
if (value <= percentiles[2]) return this.interpolate(value, percentiles[1], percentiles[2], 15, 50);
|
||||
if (value <= percentiles[3]) return this.interpolate(value, percentiles[2], percentiles[3], 50, 85);
|
||||
if (value <= percentiles[4]) return this.interpolate(value, percentiles[3], percentiles[4], 85, 97);
|
||||
return 97;
|
||||
}
|
||||
|
||||
private calculateZScore(value: number, percentiles: number[]): number {
|
||||
const median = percentiles[2]; // P50
|
||||
const sd = (percentiles[3] - percentiles[1]) / 2; // Approximate SD
|
||||
return (value - median) / sd;
|
||||
}
|
||||
|
||||
private percentileToZScore(percentile: number): number {
|
||||
// Convert percentile to z-score using inverse normal distribution
|
||||
// Simplified approximation
|
||||
if (percentile === 50) return 0;
|
||||
if (percentile === 84) return 1;
|
||||
if (percentile === 16) return -1;
|
||||
if (percentile === 97.7) return 2;
|
||||
if (percentile === 2.3) return -2;
|
||||
|
||||
// General approximation
|
||||
return (percentile - 50) / 35;
|
||||
}
|
||||
|
||||
private interpolate(
|
||||
value: number,
|
||||
x1: number,
|
||||
x2: number,
|
||||
y1: number,
|
||||
y2: number,
|
||||
): number {
|
||||
return y1 + ((value - x1) / (x2 - x1)) * (y2 - y1);
|
||||
}
|
||||
|
||||
private normalCDF(x: number): number {
|
||||
// Approximation of the cumulative distribution function for standard normal
|
||||
const t = 1 / (1 + 0.2316419 * Math.abs(x));
|
||||
const d = 0.3989423 * Math.exp((-x * x) / 2);
|
||||
const probability =
|
||||
d *
|
||||
t *
|
||||
(0.3193815 +
|
||||
t * (-0.3565638 + t * (1.781478 + t * (-1.821256 + t * 1.330274))));
|
||||
return x > 0 ? 1 - probability : probability;
|
||||
}
|
||||
|
||||
private getExpectedWeightGain(child: Child, date: Date): number {
|
||||
const ageInMonths = this.calculateAgeInMonths(child.birthDate, date);
|
||||
|
||||
// Expected monthly weight gain by age (kg/month)
|
||||
if (ageInMonths < 3) return 0.7; // 700g/month for 0-3 months
|
||||
if (ageInMonths < 6) return 0.5; // 500g/month for 3-6 months
|
||||
if (ageInMonths < 12) return 0.3; // 300g/month for 6-12 months
|
||||
if (ageInMonths < 24) return 0.2; // 200g/month for 12-24 months
|
||||
return 0.15; // 150g/month for 2+ years
|
||||
}
|
||||
|
||||
private getExpectedHeightGain(child: Child, date: Date): number {
|
||||
const ageInMonths = this.calculateAgeInMonths(child.birthDate, date);
|
||||
|
||||
// Expected monthly height gain by age (cm/month)
|
||||
if (ageInMonths < 3) return 3.5; // 3.5cm/month for 0-3 months
|
||||
if (ageInMonths < 6) return 2.0; // 2cm/month for 3-6 months
|
||||
if (ageInMonths < 12) return 1.2; // 1.2cm/month for 6-12 months
|
||||
if (ageInMonths < 24) return 0.9; // 0.9cm/month for 12-24 months
|
||||
return 0.6; // 0.6cm/month for 2+ years
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user