Fuzzy-genetic photoplethysmograph peak detection

Photoplethysmography (PPG) promises noninvasive body metrics measurement, especially that of heart rate. However, this system is prone to noise due to motion artifacts. This paper presents a fuzzy inference system, with membership functions and rules tuned by a genetic algorithm that utilizes the principal components of the PPG data accelerometer data from the x, y, and z coordinates in order to recover the peaks from the distorted PPG signal. A comparative test demonstrated that a 56.66% peak-to-peak correspondence to a reference ECG signal is achievable with the fuzzy-genetic system in place.