A Video based Heart Rate Monitoring System for Drivers Using Photoplethysmography Signal

Abstract

In this paper, a video based contactless heart rate monitoring system for a person driving a car is proposed. This system uses photoplethysmography (PPG) signal extracted from subject's face to measure his heart rate. The PPG signal acquired is effected by the illumination variation and motion artifacts that are induced when the car is moving in real life scenario. Hence, a series of filtering algorithms are applied to reduce the noise to obtain accurate heart rate. The video of subject's face is recorded for ten seconds using dashcam at a frame rate of $30fps$. The resolution of image is $640x480$ pixels. In each video frame, the subject's face is detected using Viola-Jones face detector algorithm and region of interest (ROI) is segmented to compute the average Red-Green-Blue (RGB) values. The raw PPG signal is then filtered using a series of algorithms such as signal detrending, signal normalization, illumination variation reduction, bandpass filtering, signal smoothing and Joint Approximate Diagonalization Eigenmatrices (JADE) Independent Component Analysis (ICA). Fast Fourier Transform (FFT) is used to transform the filtered PPG signal into frequency domain for peak detection. The frequency component that corresponds to the peak amplitude is the heart rate of the subject, measured in beats per minute (bpm).