Next Article in Journal
Optimization of a Series Converter for Low-Frequency Ripple Cancellation of an LED Driver
Next Article in Special Issue
A Review on the Role of Blockchain Technology in the Healthcare Domain
Previous Article in Journal
Non-Invasive Blood Glucose Monitoring Using a Curved Goubau Line
Previous Article in Special Issue
Indoor Positioning System: A New Approach Based on LSTM and Two Stage Activity Classification
Article Menu

Export Article

Open AccessArticle

Improved Heart-Rate Measurement from Mobile Face Videos

Department of Electronic Engineering, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan 48513, Korea
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(6), 663; https://doi.org/10.3390/electronics8060663
Received: 9 May 2019 / Revised: 10 June 2019 / Accepted: 10 June 2019 / Published: 12 June 2019
(This article belongs to the Special Issue Electronic Solutions for Artificial Intelligence Healthcare)
  |  
PDF [6706 KB, uploaded 12 June 2019]
  |  

Abstract

Newtonian reaction to blood influx into the head at each heartbeat causes subtle head motion at the same frequency as the heartbeats. Thus, this head motion can be used to estimate the heart rate. Several studies have shown that heart rates can be measured accurately by tracking head motion using a desktop computer with a static camera. However, implementation of vision-based head motion tracking on smartphones demonstrated limited accuracy due to the hand-shaking problem caused by the non-static camera. The hand-shaking problem could not be handled effectively with only the frontal camera images. It also required a more accurate method to measure the periodicity of noisy signals. Therefore, this study proposes an improved head-motion-based heart-rate monitoring system using smartphones. To address the hand-shaking problem, the proposed system leverages the front and rear cameras available in most smartphones and dedicates each camera to tracking facial features that correspond to head motion and background features that correspond to hand-shaking. Then, the locations of facial features are adjusted using the average point of the background features. In addition, a correlation-based signal periodicity computation method is proposed to accurately separate the true heart-rate-related component from the head motion signal. The proposed system demonstrates improved accuracy (i.e., lower mean errors in heart-rate measurement) compared to conventional head-motion-based systems, and the accuracy is sufficient for daily heart-rate monitoring. View Full-Text
Keywords: heart-rate monitoring; mobile face video; head motion analysis; hand-shaking handling; healthcare heart-rate monitoring; mobile face video; head motion analysis; hand-shaking handling; healthcare
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Lomaliza, J.-P.; Park, H. Improved Heart-Rate Measurement from Mobile Face Videos. Electronics 2019, 8, 663.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top