Heart Rate Monitoring Using PPG With Smartphone Camera
- 9 December 2021
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2985-2991
- https://doi.org/10.1109/bibm52615.2021.9669735
Abstract
Methods of estimating heart rate without the use of sensor devices provides essential benefits in both the medical field as well as the other computing applications. Smartphones are the handiest devices available to everyone today. By using videos of fingertip captured with smartphone camera, heart rate (HR) can be estimated using the photoplethysmography (PPG) technique. It is based on tracking subtle color changes on the skin owing to cardiovascular activities. These color changes are invisible to the human eye but can be detected by digital cameras. The method is divided into three main steps: first, reading the video frames and processing them to obtain the PPG data, next, extracting the Blood Volume Pulse (BVP) signal, and finally, estimating the HR from the signal. In this project, the color intensity of the skin pixels is used, and filters are applied to eliminate the noise and retain only the pulses of interest. The extracted signal is fed into a convolutional regression neural network which outputs the estimated HR. The results obtained are compared with the ground truth HR obtained by using a contact PPG sensor. We obtained a Mean Absolute Error (MAE) of 7.01 beats per minute (bpm) and an error percentage of 8.3% on test data.Keywords
This publication has 27 references indexed in Scilit:
- Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation StudyJMIR mHealth and uHealth, 2019
- Heart Rate Monitoring During Physical Exercise From Photoplethysmography Using Neural NetworkIEEE Sensors Letters, 2018
- Supervised heart rate tracking using wrist-type photoplethysmographic (PPG) signals during physical exercise without simultaneous acceleration signalsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- A survey of remote optical photoplethysmographic imaging methods2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
- Detecting Pulse from Head Motions in VideoPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- A Study of Mobile Sensing Using SmartphonesInternational Journal of Distributed Sensor Networks, 2013
- On the Analysis of Fingertip Photoplethysmogram SignalsCurrent Cardiology Reviews, 2012
- Using heart rate to control an interactive gamePublished by Association for Computing Machinery (ACM) ,2007
- Independent component analysis: algorithms and applicationsNeural Networks, 2000
- THE BLOOD SUPPLY OF VARIOUS SKIN AREAS AS ESTIMATED BY THE PHOTOELECTRIC PLETHYSMOGRAPHAmerican Journal of Physiology-Legacy Content, 1938