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Research paper | Open Access

Let home nursing assistant robots see your heart rate

Han Wu, Tao Wang( ), Tuo Dai, Xiaoyu Wang, Yuanzhen Lin, Yizhou Wang
School of Electronic Engineering and Computer Science, Peking University, Beijing, China
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Abstract

Purpose

This paper aims to design a vision-based non-contact real-time accurate heart rate (HR) measurement framework for home nursing assistant.

Design/methodology/approach

The study applied Second-Order Blind Signal Identification (SOBI) algorithm to extract remote HR signal and analyzed it with Fast Fourier Transform (FFT). Multiple regions of interest are chosen and analyzed to obtain a more accurate result.

Findings

An accurate non-contact hear rate (HR) measurement framework is proposed and proved to be efficient.

Originality/value

The contributions of this HR measurement framework are as follows: accurate measurement of HR, real-time performance, robust under various scenes such as conversation, lightweight computation which is suitable and necessary for home nursing assistance. This framework is designed to be flexibly used in various real-life scenes such as domestic health assistance and affectively intelligent agents and is proved to be robust under such scenes.

Keywords

Crowd AICrowdsourcing human-robot interaction

References

 
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Wu, H., Wang, T., Dai, T., Lin, Y. and Wang, Y. (2018), “A Real-Time Vision-Based heart rate measurement framework for home nursing assistance”, To Appear in ICAA, Vol. 2018.
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International Journal of Crowd Science
Volume 2 Issue 3,
December 2018
Pages 198-211
DOI: 10.1108/IJCS-09-2018-0023
Cite this article:
Wu H, Wang T, Dai T, et al. Let home nursing assistant robots see your heart rate. International Journal of Crowd Science, 2018, 2(3): 198-211. https://doi.org/10.1108/IJCS-09-2018-0023

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Received: 09 September 2018
Revised: 12 October 2018
Accepted: 13 October 2018
Published: 13 November 2018
© The author(s)

Han Wu, Tao Wang, Tuo Dai, Xiaoyu Wang, Yuanzhen Lin and Yizhou Wang. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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