Qwen Fitness Tracker

Track workouts, nutrition, sleep, steps, weight, goals, and streaks.

Calories In vs Out

Weight Trend

Today's Macros

Weekly Activity Minutes

Recent Logs

DateTypeDetailsValue

Log Workout

Log Daily Steps & Sleep

Recent Workouts

DateTypeIntensityMinCalDistanceHR

Log Meal

Today's Meals

MealFoodCalPCF

Recent Meals

DateMealFoodCalPCF

Log Weight & Measurements

Weight & Measurement History

DateWeight kgBody Fat %Waist cmNeck cmChest cmArm cmThigh cm

Profile & Goals

Goal Progress

Achievements

``` --- # FILE 2 — `qwen_health_analytics.html` ```html Qwen Health Analytics

Health Analytics Dashboard

SQL-backed longitudinal fitness and nutrition analytics.

1. Calorie Deficit / Surplus Over Time

Actionable Insights

    2. Workout Frequency and Intensity Trends

    4. Macro Distribution

    3. Weight Trajectory and Target Date

    6. Goal Progress Percentages

    5. Activity Streaks

    DateActivity Logged

    Goal Progress Table

    GoalProgress

    Core Schema

    CREATE TABLE users (
  id TEXT PRIMARY KEY,
  name TEXT,
  height_cm NUMERIC,
  weight_kg NUMERIC,
  start_weight_kg NUMERIC,
  goal_weight_kg NUMERIC,
  target_date DATE,
  calorie_target INT,
  protein_target INT,
  carbs_target INT,
  fat_target INT,
  step_target INT,
  sleep_target NUMERIC,
  workout_target_per_week INT
);

CREATE TABLE activities (
  id TEXT PRIMARY KEY,
  user_id TEXT REFERENCES users(id),
  date DATE,
  type TEXT,
  intensity TEXT,
  minutes NUMERIC,
  distance_km NUMERIC,
  calories_burned NUMERIC,
  steps INT,
  heart_rate_avg INT,
  notes TEXT
);

CREATE TABLE meals (
  id TEXT PRIMARY KEY,
  user_id TEXT REFERENCES users(id),
  date DATE,
  meal TEXT,
  food TEXT,
  calories INT,
  protein_g NUMERIC,
  carbs_g NUMERIC,
  fat_g NUMERIC
);

CREATE TABLE weights (
  id TEXT PRIMARY KEY,
  user_id TEXT REFERENCES users(id),
  date DATE,
  weight_kg NUMERIC,
  body_fat_pct NUMERIC
);

CREATE TABLE measurements (
  id TEXT PRIMARY KEY,
  user_id TEXT REFERENCES users(id),
  date DATE,
  waist_cm NUMERIC,
  neck_cm NUMERIC,
  chest_cm NUMERIC,
  arm_cm NUMERIC,
  thigh_cm NUMERIC
);

CREATE TABLE achievements (
  id TEXT PRIMARY KEY,
  user_id TEXT REFERENCES users(id),
  key TEXT,
  date DATE
);

    1. Calorie Deficit/Surplus Analysis Over Time

    WITH daily AS (
  SELECT user_id, date AS log_date, calories AS calories_in, 0 AS calories_out
  FROM meals
  WHERE user_id = :user_id
    AND date BETWEEN :start_date AND :end_date

  UNION ALL

  SELECT user_id, date, 0, calories_burned
  FROM activities
  WHERE user_id = :user_id
    AND date BETWEEN :start_date AND :end_date
)
SELECT
  log_date,
  SUM(calories_in) AS calories_in,
  SUM(calories_out) AS calories_out,
  SUM(calories_in) - SUM(calories_out) AS net_calories
FROM daily
GROUP BY log_date
ORDER BY log_date;

    2. Workout Frequency and Intensity Trends

    SELECT
  date_trunc('week', date) AS week,
  COUNT(*) AS workout_count,
  SUM(minutes) AS total_minutes,
  AVG(
    CASE intensity
      WHEN 'light' THEN 1
      WHEN 'moderate' THEN 2
      WHEN 'vigorous' THEN 3
      ELSE 2
    END
  ) AS avg_intensity,
  AVG(heart_rate_avg) AS avg_heart_rate
FROM activities
WHERE user_id = :user_id
  AND type NOT IN ('Steps', 'Sleep')
  AND date BETWEEN :start_date AND :end_date
GROUP BY 1
ORDER BY 1;

    3. Weight Trajectory and Target Date Calculation

    WITH trend AS (
  SELECT
    regr_slope(
      EXTRACT(EPOCH FROM date)::float,
      weight_kg
    ) AS slope
  FROM weights
  WHERE user_id = :user_id
    AND date >= CURRENT_DATE - INTERVAL '60 days'
),
latest AS (
  SELECT weight_kg
  FROM weights
  WHERE user_id = :user_id
  ORDER BY date DESC
  LIMIT 1
)
SELECT
  latest.weight_kg AS current_weight,
  :target_weight AS target_weight,
  trend.slope,
  CASE
    WHEN trend.slope < -0.001 AND :target_weight < latest.weight_kg
      THEN CURRENT_DATE + ((latest.weight_kg - :target_weight) / ABS(trend.slope))::int
    WHEN trend.slope > 0.001 AND :target_weight > latest.weight_kg
      THEN CURRENT_DATE + ((:target_weight - latest.weight_kg) / trend.slope)::int
  END AS projected_target_date
FROM trend
CROSS JOIN latest;

    4. Macro Distribution Pie Chart

    SELECT
  SUM(protein_g) * 4 AS protein_calories,
  SUM(carbs_g) * 4 AS carb_calories,
  SUM(fat_g) * 9 AS fat_calories,
  SUM(protein_g) AS protein_g,
  SUM(carbs_g) AS carbs_g,
  SUM(fat_g) AS fat_g
FROM meals
WHERE user_id = :user_id
  AND date BETWEEN :start_date AND :end_date;

    5. Activity Streaks

    WITH logged AS (
  SELECT DISTINCT date
  FROM activities
  WHERE user_id = :user_id
    AND date BETWEEN :start_date AND :end_date
    AND type <> 'Sleep'
),
grouped AS (
  SELECT
    date,
    date - ((ROW_NUMBER() OVER (ORDER BY date))::text || ' days')::interval AS grp
  FROM logged
)
SELECT
  MIN(date) AS streak_start,
  MAX(date) AS streak_end,
  COUNT(*) AS streak_days
FROM grouped
GROUP BY grp
ORDER BY streak_days DESC
LIMIT 1;

    6. Goal Progress Percentage Calculations

    WITH latest AS (
  SELECT weight_kg
  FROM weights
  WHERE user_id = :user_id
  ORDER BY date DESC
  LIMIT 1
),
daily AS (
  SELECT user_id, log_date, SUM(calories_in) AS calories_in
  FROM (
    SELECT user_id, date AS log_date, calories AS calories_in
    FROM meals
    WHERE user_id = :user_id
      AND date BETWEEN :start_date AND :end_date

    UNION ALL

    SELECT user_id, date, 0
    FROM activities
    WHERE user_id = :user_id
      AND date BETWEEN :start_date AND :end_date
  ) d
  GROUP BY user_id, log_date
)
SELECT
  u.name,
  ROUND(
    ABS(u.start_weight_kg - latest.weight_kg)
    / NULLIF(ABS(u.start_weight_kg - u.goal_weight_kg), 0)
    * 100,
    1
  ) AS weight_goal_pct,
  ROUND(
    100.0 * COUNT(*) FILTER (
      WHERE daily.calories_in BETWEEN u.calorie_target - 200 AND u.calorie_target + 200
    ) / NULLIF(COUNT(*), 0),
    1
  ) AS calorie_adherence_pct
FROM users u
CROSS JOIN latest
LEFT JOIN daily ON daily.user_id = u.id
WHERE u.id = :user_id
GROUP BY u.name, latest.weight_kg;