Suryasari Suryasari, Aminuddin Rizal, Sri Kusumastuti, Taufiqqurrachman Taufiqqurrachman
{"title":"Illuminance Color Independent in Remote Photoplethysmography for Pulse Rate Variability and Respiration Rate Measurement","authors":"Suryasari Suryasari, Aminuddin Rizal, Sri Kusumastuti, Taufiqqurrachman Taufiqqurrachman","doi":"10.30630/joiv.7.3.1176","DOIUrl":null,"url":null,"abstract":"Remote photoplethysmography (rPPG) is now becoming a new trend method to measure human physiological parameters. Especially due to it noncontact measurement which safe dan suitable to use in this new era condition. Pulse rate variability (PRV) and respiration rate (RR) included as parameters can be measured by using rPPG. PRV and RR are used to measure both physical and psychological wellness of the subject. However, current performance challenges in rPPG algorithm in measuring PRV and RR are illuminance invariant and motion. Especially in different light condition which represent real-life environment, signal-to-noise ratio (SNR) will be affected and directly reduce the measurement accuracy. Therefore in this study, we develop rPPG algorithm and then investigate the performance rPPG in different illuminance scenarios. We perform PRV and RR measurement under each scenario. On this study, for the pulse signal extraction, we were using algorithm is based on the modification of plane orthogonal-to-skin (POS) algorithm. While, for respiration signal extraction is done in CIE Lab color space. Our experimental results show the mean absolute error (MAE) of each measured parameters are 3.25 BPM and 2 BPM for PRV and RR respectively compared with clinical apparatus. The proposed method proved to be more reliable to use in real environments measurement. However, limitation of our proposed algorithm is still running in offline mode, hence for the future we want try to make our algorithm run in real time.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"366 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOIV International Journal on Informatics Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30630/joiv.7.3.1176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Remote photoplethysmography (rPPG) is now becoming a new trend method to measure human physiological parameters. Especially due to it noncontact measurement which safe dan suitable to use in this new era condition. Pulse rate variability (PRV) and respiration rate (RR) included as parameters can be measured by using rPPG. PRV and RR are used to measure both physical and psychological wellness of the subject. However, current performance challenges in rPPG algorithm in measuring PRV and RR are illuminance invariant and motion. Especially in different light condition which represent real-life environment, signal-to-noise ratio (SNR) will be affected and directly reduce the measurement accuracy. Therefore in this study, we develop rPPG algorithm and then investigate the performance rPPG in different illuminance scenarios. We perform PRV and RR measurement under each scenario. On this study, for the pulse signal extraction, we were using algorithm is based on the modification of plane orthogonal-to-skin (POS) algorithm. While, for respiration signal extraction is done in CIE Lab color space. Our experimental results show the mean absolute error (MAE) of each measured parameters are 3.25 BPM and 2 BPM for PRV and RR respectively compared with clinical apparatus. The proposed method proved to be more reliable to use in real environments measurement. However, limitation of our proposed algorithm is still running in offline mode, hence for the future we want try to make our algorithm run in real time.