Dual Wavelength Photoplethysmography Framework for Heart Rate Calculation

Area of Science:

• Biomedical Engineering
• Physiological Monitoring
• Signal Processing

Background:

• Photoplethysmography (PPG) signal quality for heart rate (HR) extraction degrades with motion.
• Current methods often rely on auxiliary signals like accelerometers to mitigate motion artifacts.
• Previous noise-component denoising techniques were limited to minor movements.

Purpose of the Study:

• To extend PPG-based HR calculation to high-intensity, full-body motion.
• To introduce and validate the Dual Wavelength (DWL) framework for robust HR estimation.
• To assess the efficacy of DWL in eliminating the need for auxiliary motion sensors.

Main Methods:

• Developed a Dual Wavelength (DWL) framework utilizing noise components from infrared PPG to denoise green PPG signals.
• Collected PPG data from 14 participants during treadmill running (high-intensity macro-motion).
• Compared DWL performance against accelerometer-dependent methods (TROIKA, JOSS).

Main Results:

• DWL demonstrated high accuracy in HR calculation during intense motion, outperforming existing methods.
• The DWL framework successfully operated using only PPG signals, negating the need for accelerometers.
• Achieved a Mean Absolute Error (MAE) of 1.22±0.57 BPM and a performance index (PI) of 95.88±4.9%.
• Demonstrated computational efficiency with a processing time of 3.0±0.3 seconds for a 360-second run.

Conclusions:

• The DWL framework enables accurate HR calculation from PPG signals even under significant motion.
• DWL offers a sensor-efficient and computationally effective solution for wearable HR monitoring.
• This technique advances PPG-based physiological monitoring for dynamic activities.