Automated Heart Rate Measurement Using Wavelet Analysis of Face Video Sequences

To overcome the drawbacks of the conventional heart rate measurement method, a new approach is developed to measure cardiac pulse automatically using video imaging technique and wavelet analysis. In this paper, the color video images of the human face are used for detection of cardiac pulses. The specific region of interest (ROI) in face image is detected to obtain red, green, and blue intensity signals. Next normalized red, green, and blue intensity signals are decomposed using discrete wavelet transform (DWT) to obtain approximate and detail coefficients. Then, the specific frequency band from decomposed signal is obtained with the help of bandpass filter using Hamming window function. The cardiac pulse is measured with the help of pulse frequency in power density spectrum of filtered signal. The cardiac pulse measured with help of this system is compared with heart rate measured from reference ECG signal of the same object. This technique improves the accuracy from 73.14 to 89.86% if forehead of the subject is considered instead of face.