Muhammad Farooq, Syed Aziz Shah, Dingchang Zheng, Ahmad Taha, Muhammad Imran, Qammer H Abbasi, Hasan Tahir Abbas
{"title":"利用雷达信号的高级信号处理技术进行非接触式心音检测。","authors":"Muhammad Farooq, Syed Aziz Shah, Dingchang Zheng, Ahmad Taha, Muhammad Imran, Qammer H Abbasi, Hasan Tahir Abbas","doi":"10.1109/JBHI.2024.3490992","DOIUrl":null,"url":null,"abstract":"<p><p>Contactless vital signs detection has the potential to advance healthcare by offering precise and convenient patient monitoring. This groundbreaking approach not only streamlines the monitoring process, but also allows continuous, real-time assessment of vital signs, allowing early detection of anomalies and prompt intervention. This paper presents a novel framework for contactless vital signs detection using continuous-wave (CW) radar and advanced signal processing techniques. We achieved unprecedented precision in capturing 1,261 samples for radar based heart sound waveforms compared to the ground truth ECG signal. Further, our heart sounds method yields highly accurate human heart pulse readings, surpassing previous benchmarks with a mean absolute percentage error (MAPE) of 0.0129 and mean absolute error (MAE) below one (0.8712). In addition, we derived heart rates from the heart sound waveforms and compare them with conventional radar-derived heart rates and ground truth ECG signal. Through analysis, we identified regions where conventional radar based methods exhibit limitations. Our approach demonstrates minimal errors and superior accuracy across all heart rate states, which can potentially set new standards for noninvasive vital sign monitoring.</p>","PeriodicalId":13073,"journal":{"name":"IEEE Journal of Biomedical and Health Informatics","volume":"PP ","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Contactless Heart Sound detection using Advanced Signal Processing Exploiting Radar Signals.\",\"authors\":\"Muhammad Farooq, Syed Aziz Shah, Dingchang Zheng, Ahmad Taha, Muhammad Imran, Qammer H Abbasi, Hasan Tahir Abbas\",\"doi\":\"10.1109/JBHI.2024.3490992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Contactless vital signs detection has the potential to advance healthcare by offering precise and convenient patient monitoring. This groundbreaking approach not only streamlines the monitoring process, but also allows continuous, real-time assessment of vital signs, allowing early detection of anomalies and prompt intervention. This paper presents a novel framework for contactless vital signs detection using continuous-wave (CW) radar and advanced signal processing techniques. We achieved unprecedented precision in capturing 1,261 samples for radar based heart sound waveforms compared to the ground truth ECG signal. Further, our heart sounds method yields highly accurate human heart pulse readings, surpassing previous benchmarks with a mean absolute percentage error (MAPE) of 0.0129 and mean absolute error (MAE) below one (0.8712). In addition, we derived heart rates from the heart sound waveforms and compare them with conventional radar-derived heart rates and ground truth ECG signal. Through analysis, we identified regions where conventional radar based methods exhibit limitations. Our approach demonstrates minimal errors and superior accuracy across all heart rate states, which can potentially set new standards for noninvasive vital sign monitoring.</p>\",\"PeriodicalId\":13073,\"journal\":{\"name\":\"IEEE Journal of Biomedical and Health Informatics\",\"volume\":\"PP \",\"pages\":\"\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Biomedical and Health Informatics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1109/JBHI.2024.3490992\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Biomedical and Health Informatics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/JBHI.2024.3490992","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Contactless Heart Sound detection using Advanced Signal Processing Exploiting Radar Signals.
Contactless vital signs detection has the potential to advance healthcare by offering precise and convenient patient monitoring. This groundbreaking approach not only streamlines the monitoring process, but also allows continuous, real-time assessment of vital signs, allowing early detection of anomalies and prompt intervention. This paper presents a novel framework for contactless vital signs detection using continuous-wave (CW) radar and advanced signal processing techniques. We achieved unprecedented precision in capturing 1,261 samples for radar based heart sound waveforms compared to the ground truth ECG signal. Further, our heart sounds method yields highly accurate human heart pulse readings, surpassing previous benchmarks with a mean absolute percentage error (MAPE) of 0.0129 and mean absolute error (MAE) below one (0.8712). In addition, we derived heart rates from the heart sound waveforms and compare them with conventional radar-derived heart rates and ground truth ECG signal. Through analysis, we identified regions where conventional radar based methods exhibit limitations. Our approach demonstrates minimal errors and superior accuracy across all heart rate states, which can potentially set new standards for noninvasive vital sign monitoring.
期刊介绍:
IEEE Journal of Biomedical and Health Informatics publishes original papers presenting recent advances where information and communication technologies intersect with health, healthcare, life sciences, and biomedicine. Topics include acquisition, transmission, storage, retrieval, management, and analysis of biomedical and health information. The journal covers applications of information technologies in healthcare, patient monitoring, preventive care, early disease diagnosis, therapy discovery, and personalized treatment protocols. It explores electronic medical and health records, clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, and more. Integration-related topics like interoperability, evidence-based medicine, and secure patient data are also addressed.