Robust RPPG Method Based on Reference Signal Envelope to Improve Wave Morphology

Author:

Sun Lu1ORCID,Wang Liting2,Shen Wentao2,Liu Changsong2,Bai Fengshan1

Affiliation:

1. Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China

2. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China

Abstract

Remote physiological monitoring has become increasingly important in improving quality of life, with remote photoplethysmography (RPPG) being a popular choice. This paper introduces an envelope–based method for RPPG channels to improve wave morphology of the collected signal based on the reference signal from finger PPG. Using a model consistent with physiological and optical principles, the authors divided the signal into linear superpositions, comprising pulse, constant, and disturbance components. The correlation coefficients were used to calculate a linear combination of Red–Green–Blue (RGB) channels to approximate the envelope shape of the reference PPG signal. Experiments with different light intensities and stability were designed to compare the envelope approximation ability and robustness of the proposed method with some common methods. Analysis of variance demonstrated the stable performance of the envelopment–based approach in most cases. Additionally, it improved the morphology of the Green (G) channel, including changing trends and directions, adjusting wave sizes, reducing noise, and reinforcing details of the single waveform. The envelope–based linear model approach has the ability to flexibly improve RPPG signals, which helps RPPG play a full role in many fields such as medicine.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3