What do all those health metrics on your watch actually mean? Is a low heart rate variability a sign of illness? What’s a normal blood oxygen level? How accurate is sleep tracking? This guide explains health data from a physiological and sensor technology perspective.
1. Interpreting Heart Rate Data
Resting Heart Rate (RHR)
- Normal Range: 60-100 bpm
- Excellent: 50-60 bpm (for trained individuals)
- Reasons for High RHR:
- Stress/Anxiety → Sympathetic nervous system activation
- Lack of sleep → Autonomic nervous system imbalance
- Dehydration → Decreased blood volume → Compensatory heart rate increase
- Infection/Fever → Increased metabolism
- Caffeine → Sympathetic nervous system stimulation
- Reasons for Low RHR:
- Long-term aerobic training → Improved cardiac efficiency
- High vagal tone → Parasympathetic dominance
- Certain medications → Beta-blockers
- Focus on Trends: A single reading has limited meaning → Long-term trends are more important → A sustained increase of 5-10 bpm in RHR may indicate overtraining or illness
Heart Rate Variability (HRV)
- Definition: The variation in time intervals between consecutive heartbeats → Reflects autonomic nervous system function
- Measurement: RMSSD method (most common) → Unit: ms
- Reference Ranges:
| Population | HRV Range (RMSSD) |
|---|---|
| Young, Healthy | 40-100 ms |
| Middle-aged, Healthy | 25-60 ms |
| Elderly | 15-40 ms |
| High-level Athletes | 60-150 ms+ |
- High HRV: Parasympathetic nervous system is active → Good recovery → Optimal physical state
- Low HRV: Sympathetic nervous system is dominant → High stress / Overtraining / Illness / Poor sleep
- Applications:
- Check HRV before training → High = can handle high intensity → Low = should rest or do light exercise
- Daily HRV trends → Assess body recovery status
- Note: HRV varies greatly between individuals → Focus on your own baseline and trends → Don't compare with others
Exercise Heart Rate Zones
- See running training guides → Z1-Z5 zones → The foundation of scientific training
2. Blood Oxygen Saturation (SpO2)
Measurement Principle
- PPG Photoplethysmography:
- Red light (660 nm) → Highly absorbed by deoxygenated hemoglobin
- Infrared light (940 nm) → Highly absorbed by oxygenated hemoglobin
- Calculates the absorption ratio of the two lights → Estimates SpO2
Normal Values
| SpO2 | Status | Recommendation |
|---|---|---|
| 95-100% | Normal | No action needed |
| 90-95% | Mild Hypoxia | Monitor + Deep breathing |
| <90% | Significant Hypoxia | Seek medical attention! |
| <80% | Severe Hypoxia | Emergency medical attention! |
Watch SpO2 Accuracy
- Comparison with Medical Fingertip Pulse Oximeters: Error margin of ±2-3%
- Factors Affecting Accuracy:
- Strap tightness → Too loose = poor signal
- Tattoos → Interfere with light signals
- Movement → Signal interference
- Skin temperature → Cold = reduced blood flow = weak signal
- Note: Watch SpO2 is for reference only → Not for medical diagnosis
High-Altitude Application
- At altitudes of 3000m+ → A drop in SpO2 is a normal physiological response
- SpO2 <85% + Headache → Sign of Acute Mountain Sickness → Requires descent
3. Interpreting Sleep Data
Sleep Stages
| Stage | Percentage | Characteristics | Function |
|---|---|---|---|
| Light Sleep (N1+N2) | 50-60% | Heart rate drops, body temperature drops | Transition phase |
| Deep Sleep (N3/Slow Wave Sleep) | 15-25% | Lowest heart rate, hardest to wake | Physical repair, growth hormone secretion |
| REM Sleep | 20-25% | Heart rate fluctuates, rapid eye movements | Memory consolidation, emotional regulation |
Watch Sleep Tracking Principles
- Accelerometer: Detects body movement → No movement = Deep Sleep/REM, slight movement = Light Sleep
- Heart Rate: Deep sleep has the lowest and most stable heart rate → REM shows heart rate fluctuations
- HRV: Deep sleep has the highest HRV → Parasympathetic dominance
Sleep Data Accuracy
- Stage Classification Accuracy: Approximately 70-80% (compared to PSG polysomnography)
- Relatively Accurate: Total sleep time → Quite accurate
- Less Accurate: Specific duration of Deep Sleep/REM → May have errors
- Most Valuable Metrics: Total sleep time + Sleep regularity → More practical than stage analysis
Key Points for Sleep Score
- Total Duration: 7-9 hours → Recommended for adults
- Regularity: Going to bed and waking up at the same time daily → More important than total duration
- Deep Sleep Percentage: 15-25% is normal → Too low = insufficient physical repair
- Sleep Disruptions: Frequent awakenings → Poor sleep quality → Even if total duration is sufficient
4. Stress and Recovery Data
Stress Score
- Principle: Based on HRV analysis → Balance between sympathetic/parasympathetic systems
- Score Range: 0-100
- 0-25: Relaxed
- 26-50: Low stress
- 51-75: Moderate stress
- 76-100: High stress
- Use Cases:
- When stress is high → Deep breathing exercises → 5 minutes of diaphragmatic breathing → Effectively lowers stress
- Sustained high stress → Needs lifestyle adjustment
Body Battery / Recovery Index
- Principle: Combines HRV + Sleep + Activity level → Estimates body recovery status
- Application:
- High battery → Can handle high-intensity training
- Low battery → Should rest or do light activity
- Note: This is an estimate → Don't rely on it excessively → Combine with your own feelings
5. Interpreting Exercise Data
VO2max Estimation
- Principle: Based on the relationship between heart rate and pace during running/walking → Estimates maximal oxygen uptake
- Accuracy: Error margin of ±5-10% → Trends are more meaningful than absolute values
- Reference Values:
| Gender | Poor | Fair | Good | Excellent |
|---|---|---|---|---|
| Male | <35 | 35-43 | 44-51 | >51 |
| Female | <27 | 27-34 | 35-43 | >43 |
Training Load
- Acute Load: Training volume over the last 7 days
- Chronic Load: Training volume over the last 28 days
- Load Ratio: Acute / Chronic
- 0.8-1.3 → Optimal → Training is effective and safe
-
1.5 → Significantly increased injury risk
- <0.8 → Insufficient training
Training Effect
- Aerobic Effect: 0-5 points → 3-4 indicates effective training → 5 may indicate overtraining
- Anaerobic Effect: 0-5 points → Only interval training can improve this
6. Data Privacy and Security
Sensitivity of Health Data
- Heart rate / Sleep / Location → Highly personal privacy
- Health insurance companies could use data → Affecting premiums
- Employers could access data → Affecting employment
Protection Recommendations
- Read the Privacy Policy → Understand how data is used
- Disable Unnecessary Data Sharing → Location / Social features
- Regularly Export and Back Up Data → Avoid being locked into a platform
- Be Cautious with Third-Party Apps → Each authorization is a potential data leak risk
7. Common Misconceptions
- ❌ "Watch data is 100% accurate" → All data has error margins → Focus on trends, not absolute values
- ❌ "An abnormal reading means I'm sick" → A single anomaly is meaningless → Only persistent anomalies warrant concern
- ❌ "A watch can replace a medical checkup" → A watch is a supportive tool → It cannot replace medical diagnosis
- ❌ "A low HRV compared to others means I'm unhealthy" → HRV varies greatly between individuals → Compare with yourself
- ✅ Data is for supporting decisions → Training planning, lifestyle adjustments
- ✅ Persistent anomalies → Seek medical attention promptly → The watch is a reminder, not a diagnosis
A smartwatch is a tool for health management, not a substitute for a doctor. Understand the data, focus on trends, and apply it wisely. Let technology help you better understand your body. But remember: the best health monitor is how you feel—rest when you're tired, and see a doctor if something feels wrong!