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README_DATA.md

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+# Sample Diabetes Data - Test Your App! 📊
+
+## 📁 File: `sample_diabetes_data.csv`
+
+This is **realistic synthetic CGM data** for a full day (24 hours) with interesting events!
+
+---
+
+## 🎯 What's in the Data
+
+### Timeline: January 15, 2025 (6:00 AM - 11:55 PM)
+**200 data points** @ 5-minute intervals
+
+### Key Events to Watch For:
+
+#### 1. **Morning Hypo Risk** (6:00 AM - 7:20 AM)
+- Glucose drops from 95 → 80 mg/dL
+- **Alert should trigger** around 7:15 AM
+- **Breakfast bolus**: 45g carbs + 4.5u insulin at 7:20 AM
+- Recovery to 128 mg/dL
+
+#### 2. **Post-Breakfast Spike** (7:20 AM - 8:30 AM)
+- Glucose rises to 128 mg/dL
+- Gradual descent back to normal range
+
+#### 3. **Morning Exercise** (10:30 AM - 12:00 PM)
+- Heart rate increases (65 → 130 BPM)
+- Steps accumulate rapidly
+- Glucose stays stable due to activity
+
+#### 4. **Lunch Spike** (12:00 PM - 1:15 PM)
+- **Large meal**: 60g carbs + 6u insulin
+- Glucose spikes to **176 mg/dL** (near hyper threshold)
+- **Alert should trigger** around 1:00 PM
+- Gradual descent over 3 hours
+
+#### 5. **Late Afternoon Stability** (3:00 PM - 6:00 PM)
+- Glucose stable in target range (100-110 mg/dL)
+- Minimal significance scores expected
+
+#### 6. **Dinner** (6:00 PM - 7:00 PM)
+- 55g carbs + 5.5u insulin
+- Moderate spike to 159 mg/dL
+- Controlled descent
+
+#### 7. **SEVERE HYPO EVENT** ⚠️ (10:00 PM)
+- **CRITICAL**: Glucose drops to **15 mg/dL**!
+- Overcorrection with 3u insulin (mistake scenario)
+- **Multiple alerts expected**
+- Emergency 15g carbs consumed
+- Recovery to safe levels
+
+#### 8. **Overnight Stability** (11:00 PM onwards)
+- Glucose settles around 100 mg/dL
+- Normal sleep HR (52-60 BPM)
+
+---
+
+## 🧪 Expected Results
+
+### Activation Patterns:
+- **High activation**: During hypo (7:15 AM, 10:00 PM), hyper (1:00 PM)
+- **Low activation**: Stable periods (3-6 PM, after 11 PM)
+- **Target activation rate**: ~15-20% overall
+
+### Alerts Expected:
+Approximately **3-5 high-risk alerts**:
+1. Morning hypo warning (~7:15 AM)
+2. Lunch hyper warning (~1:00-1:15 PM)
+3. **CRITICAL hypo** (~10:00-10:20 PM) - multiple alerts
+
+### Energy Savings:
+- **~80-85%** energy saved vs always-on
+- Most savings during stable periods
+- More activations during risk events
+
+### Significance Components:
+Watch how they change:
+- **Glycemic deviation**: High during hypo/hyper
+- **Velocity risk**: Spikes during rapid changes
+- **IOB risk**: High after insulin doses
+- **COB risk**: High after meals
+- **Activity risk**: Elevated during exercise
+- **Variability**: Shows instability during events
+
+---
+
+## 🎮 How to Test
+
+### Option 1: Local App
+```bash
+cd "C:\Users\adminidiakhoa\sundew_algorithms\HULL_use\diabetes\sundew_diabetes_watch"
+streamlit run app_advanced.py
+```
+
+1. **Uncheck** "Use synthetic example"
+2. Click "Browse files"
+3. Upload `sample_diabetes_data.csv`
+4. Watch the magic! ✨
+
+### Option 2: Hugging Face Space
+1. Visit: https://huggingface.co/spaces/mgbam/sundew_diabetes_watch
+2. Upload `sample_diabetes_data.csv`
+3. Explore the visualizations
+
+---
+
+## 🔍 What to Look For
+
+### 1. Performance Dashboard
+- Total events: **200**
+- Activations: **30-40** (15-20%)
+- Energy savings: **80-85%**
+- Alerts: **3-5**
+
+### 2. Glucose Chart
+- See the full day pattern
+- Identify meal spikes
+- Spot hypo events
+
+### 3. Significance vs Threshold
+- **Watch the PI controller adapt!**
+- Threshold moves to maintain 15% activation
+- Significance spikes during risk events
+
+### 4. Energy Level
+- **Bio-inspired regeneration** visible
+- Drops during activations
+- Regenerates during idle periods
+- Should fluctuate, not flat
+
+### 5. Significance Components
+- **6 colored lines** showing risk factors
+- Glycemic deviation dominates during extremes
+- Velocity spikes during rapid changes
+- IOB/COB after meals
+
+### 6. Alerts Table
+Look for warnings around:
+- 7:15 AM (morning hypo approach)
+- 1:00 PM (post-lunch hyper)
+- 10:05-10:20 PM (critical hypo)
+
+### 7. Bootstrap Confidence Intervals
+- F1 Score with 95% CI
+- Precision with 95% CI
+- Recall with 95% CI
+- Check that CI ranges are reasonable
+
+---
+
+## 📊 Advanced Analysis
+
+### Export Telemetry
+1. Check "Export Telemetry JSON"
+2. Download `sundew_diabetes_telemetry.json`
+3. Contains all 200 events with full details
+4. Use for:
+   - Hardware power measurement correlation
+   - Detailed analysis in Excel/Python
+   - Custom visualizations
+   - Research papers
+
+### Compare Presets
+Try different Sundew configurations:
+
+**`custom_health_hd82`** (Recommended for diabetes)
+- 82% energy savings target
+- Healthcare-optimized
+- Expect: High recall, lower precision
+
+**`tuned_v2`** (Balanced)
+- General purpose
+- Good balance
+- Expect: Medium recall/precision
+
+**`conservative`** (Maximum savings)
+- Minimal activations
+- Expect: Lower recall, higher savings
+
+**`aggressive`** (Maximum safety)
+- More activations
+- Expect: Higher recall, lower savings
+
+---
+
+## 📝 Data Format
+
+**Columns:**
+- `timestamp`: DateTime in ISO format
+- `glucose_mgdl`: Blood glucose in mg/dL (40-400 range)
+- `carbs_g`: Carbohydrate intake in grams (0-60)
+- `insulin_units`: Insulin dosage in units (0-6)
+- `steps`: Cumulative step count (0-1065)
+- `hr`: Heart rate in BPM (48-130)
+
+**Frequency**: 5-minute intervals (standard CGM)
+
+**Duration**: 18 hours (6 AM - 12 AM)
+
+---
+
+## 🎯 Challenge Yourself
+
+### Can You Spot:
+1. The exact time glucose crosses below 70 mg/dL?
+2. How long it takes to recover from the severe hypo?
+3. Which meal caused the highest glucose spike?
+4. When the PI controller adjusts threshold most dramatically?
+5. The period with lowest energy consumption?
+
+### Experiment With:
+- Different target activation rates (5%, 15%, 30%)
+- Different energy pressure values
+- Different hypo/hyper thresholds
+- Different Sundew presets
+
+---
+
+## 🌟 Pro Tips
+
+1. **Enable all visualizations** for full effect
+2. **Watch the threshold adapt** in real-time (Significance vs Threshold chart)
+3. **Check the 10 PM hypo** - algorithm should light up!
+4. **Export telemetry** to see component breakdown
+5. **Try bootstrap CI** for statistical rigor
+
+---
+
+## 🎓 Learning Outcomes
+
+After testing with this data, you'll understand:
+
+✅ How Sundew adapts threshold to maintain target activation
+✅ How 6-factor significance scoring works
+✅ How energy regeneration creates sustainable monitoring
+✅ How bootstrap CI provides statistical confidence
+✅ How ensemble models improve predictions
+✅ How alerts trigger during real risk events
+
+---
+
+## 🚀 Next Steps
+
+1. **Test with this data** to verify app works
+2. **Create your own data** with different patterns
+3. **Compare results** across different presets
+4. **Export telemetry** for deeper analysis
+5. **Share results** with your network!
+
+---
+
+**This data showcases the algorithm at its finest!** 🌿✨
+
+The severe hypo at 10 PM will really make Sundew **SHINE**!