Developing a Wireless, High Precision and Processing Speed Pulse Monitoring Headset Using Photoplethysmography

Area of Science:

• Biomedical Engineering
• Signal Processing
• Optical Sensing

Background:

• Pulse wave acquisition is crucial for health monitoring.
• Existing systems face challenges with noise, baseline drift, and sensor accuracy.
• Optimizing signal acquisition at the earlobe requires careful consideration of optical properties.

Purpose of the Study:

• To present a thoroughly improved pulse monitoring and analysis system with a headset structure.
• To determine the optimal infrared wavelength for earlobe pulse wave acquisition using Monte Carlo simulation.
• To enhance system accuracy and processing speed for practical health management applications.

Main Methods:

• Monte Carlo simulation to identify optimal infrared wavelength.
• Software-based compensation for sensor dimensional drift.
• Nonlinear quantization and table look-up with interpolation for signal analysis.
• Development of a headset-based pulse monitoring device.

Main Results:

• Optimized infrared wavelength selection for earlobe pulse acquisition.
• Effective compensation for high-frequency noise, baseline drift, and sensor drift.
• A novel, rapid signal analysis method achieving ~30x speed improvement over FFT.
• Demonstrated high accuracy with a maximum residual of < 0.004 mV and high correlation with reference measurements.

Conclusions:

• The developed headset system provides precise and rapid pulse monitoring.
• The system's accuracy and speed make it suitable for widespread use in health management and medical measurement.
• This work offers a practical solution for advanced physiological signal acquisition.