Optimization of multi-wavelength Photoplethysmographic for wearable heart rate acquisition

Abstract

Photoplethysmographic is an optical measure technique for heart rate monitoring on the surface of the skin. PPG based wearable heart rate monitor has become popular in consumer targeted market. This thesis work is based on the PulseOn product development and the final implementation will be integrated into the PulseOn OHRM sensor product.

Choice of the wavelength of PPG is a trade-off between power consumption and accuracy considering the activity type, skin color and skin perfusion. The subject of this thesis is implementing a channel selection algorithm, which is green and IR channel, on a commercially available PulseOn wrist band to optimize the power consumption and accuracy of the measurement. The channel selection algorithm is first implemented and evaluated in Matlab simulation and then implemented in C code.

Performance of the channel selection algorithm on the device is evaluated considering various factors, including skin color, tightness of the wristband. The results show that channel selection algorithm can not only reduce the power consumption but also help to handle the measurement on different measurement conditions.