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.
KeywordsCardiac pulse Discrete wavelet transform (DWT) Face detection Power spectrum density (PSD)
All authors are thankful to all the participants and the Principal Dr. M. B. Khambete of MKSSS Cummins College of Engineering for Women Karvenagar, Pune for the support.
Compliance with Ethical Standard
All procedures performed in this study involving human participants were in accordance with ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants involved in the study.
- 1.Cromwell L, Weibell FJ, Pfeiffer EA (2017) Biomedical instrumentation and measurements, 2nd edn. PHI Learning Private Limited, DelhiGoogle Scholar
- 2.Carr JJ, Brown JM (2015) Introduction to biomedical equipment technology, 4th edn. Pearson PublicationGoogle Scholar
- 4.Lewandowska M, Ruminski J, Kocejko T (2011) Measuring pulse rate with a webcam—a non-contact method for evaluating cardiac activity. In: Proceedings of the federated conference on computer science and information systems, pp 405–410Google Scholar
- 5.Gault TR, Farag AA (2013) Fully automatic method to extract the heart rate from thermal video. In: Computer vision and pattern recognition workshops (CVPRW), IEEE conference, pp 2160–7516, Sept 2013Google Scholar
- 8.Proakis JG, Manolakis DG (2012) Digital signal processing: principles, algorithms and applications, 4th edn. Pearsons Publication, 2012Google Scholar