cHRV Uncovering Daily Stress Dynamics Using Bio-Signal from Consumer Wearables

Area of Science:

• Smart and connected health
• Biomedical engineering
• Wearable technology

Background:

• Effective stress management requires understanding daily stress dynamics.
• Current methods for real-time, longitudinal stress monitoring are often impractical or obtrusive.
• Consumer wearables commonly use photoplethysmography (PPG) sensors for heart rate monitoring.

Purpose of the Study:

• To develop a convenient, low-maintenance heart rate variability (HRV)-based biomarker named cHRV for reliable stress dynamics reflection.
• To enable unobtrusive, day-to-day stress monitoring using readily available wearable technology.

Main Methods:

• Derived a novel cHRV biomarker using photoplethysmography (PPG) sensor data.
• Conducted 14 controlled in-lab experiments to evaluate cHRV feasibility and performance.
• Assessed the correlation between cHRV and actual stress dynamics.

Main Results:

• The proposed cHRV biomarker demonstrated a strong correlation (r > 0.95) with stress dynamics.
• cHRV calculations are efficient and practical, requiring only PPG sensor data.
• The biomarker is suitable for integration into mainstream consumer wearables.

Conclusions:

• cHRV shows significant potential as a reliable biomarker for continuous stress assessment.
• The practicality and low-maintenance nature of cHRV make it ideal for widespread adoption in daily stress monitoring.
• Leveraging PPG data from wearables facilitates unobtrusive, long-term stress tracking.