Paper Info
Title
Real-time quantifying heart beat rate from facial video recording on a smart phone using Kalman filters
Abstract
Photoplethysmography (PPG) can be carried out through facial video recording by a smart phone camera in ambient light. The main challenge is to eliminate motion artifacts and ambient noise. We describe a real-time algorithm to quantify the heart beat rate from facial video recording captured by the camera of a smart phone. We extract the green channel from the video. Then we normalize it and use a Kalman filter with a particular structure to eliminate ambient noise. This filter also enhances the heart pulse component in the signal distorted by Gaussian noise and white noise. After that we employ a band-pass FIR filter to remove the remaining motion artifacts. This is followed by peak detection or Lomb periodogram to estimate heart rate. The algorithm has low computational overhead, low delay and high robustness, making it suitable for real-time interaction on a smart phone. Finally we describe an Android application based on this study.
Year
DOI
Venue
2014
10.1109/HealthCom.2014.7001875
Healthcom
Keywords
Field
DocType
band-pass fir filter,heart beat rate,video signal processing,kalman filter,photoplethysmography,cardiology,kalman filters,heart pulse component,green channel,lomb periodogram,motion artifact elimination,facial video recording,android application,medical signal processing,motion artifact,smart phone,fir filters,real time,white noise,video recording,gaussian noise,smart phones,ppg,smart phone camera,band-pass filters,peak detection,real time systems,noise
Data mining,Overhead (computing),Computer science,Ambient noise level,White noise,Robustness (computer science),Artificial intelligence,Finite impulse response,Computer vision,Communication channel,Kalman filter,Speech recognition,Gaussian noise
Conference
Citations 
PageRank 
References 
2
0.39
6
Authors
4
Name
Order
Citations
PageRank
Wenjun Jiang135624.25
Shi Chao Gao220.39
Peter Wittek320.39
Li Zhao420.39