Hoang Thi Yen;Masaki Kurosawa;Tetsuo Kirimoto;Yukiya Hakozaki;Takemi Matsui;Guanghao Sun
{"title":"基于时频域分析的连续波雷达心跳间隔和心率变异性非接触估计","authors":"Hoang Thi Yen;Masaki Kurosawa;Tetsuo Kirimoto;Yukiya Hakozaki;Takemi Matsui;Guanghao Sun","doi":"10.1109/JERM.2023.3326562","DOIUrl":null,"url":null,"abstract":"Vital signs are objective indices of health status. Heart rate variability (HRV) is the physiological phenomenon of variation in interval between consecutive heartbeats, which carries more physiological information than respiration rate (RR) or heart rate (HR). Medical radar isa potential sensor for non-contact vital sign monitoring. However, this sensor requires a more complicated process for HRV extraction. In this study, the HRV was obtained as follows: The heartbeat component was extracted from the radar signal using a locally projected noise reduction (LPNR)-based nonlinear adaptive filter and a convolution-based smoothing filter. The heartbeat component still includes undesired peaks; therefore, a derivative function was used to detect the sharpest slope peak, which is the desired peak, followed by R-peak detection to obtain HRV. To evaluate the performance of the proposed method, we tested the system on 18 healthy subjects and compared the HRV determined by this sensor with that measured by contact-type electrocardiography (ECG). The results show a correlation of 97.43% between HRV by radar and HRV by ECG; the 95% confidence of inter-beat interval (IBI) is 59.5 ms. In addition, the proposed method was applied to monitor the change in HRV of an inpatient from Yokohama Hospital, Japan. The clinical data processing results provided consent for the nurse's daily check.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"7 4","pages":"457-467"},"PeriodicalIF":3.0000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Non-Contact Estimation of Cardiac Inter-Beat Interval and Heart Rate Variability Using Time-Frequency Domain Analysis for CW Radar\",\"authors\":\"Hoang Thi Yen;Masaki Kurosawa;Tetsuo Kirimoto;Yukiya Hakozaki;Takemi Matsui;Guanghao Sun\",\"doi\":\"10.1109/JERM.2023.3326562\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vital signs are objective indices of health status. Heart rate variability (HRV) is the physiological phenomenon of variation in interval between consecutive heartbeats, which carries more physiological information than respiration rate (RR) or heart rate (HR). Medical radar isa potential sensor for non-contact vital sign monitoring. However, this sensor requires a more complicated process for HRV extraction. In this study, the HRV was obtained as follows: The heartbeat component was extracted from the radar signal using a locally projected noise reduction (LPNR)-based nonlinear adaptive filter and a convolution-based smoothing filter. The heartbeat component still includes undesired peaks; therefore, a derivative function was used to detect the sharpest slope peak, which is the desired peak, followed by R-peak detection to obtain HRV. To evaluate the performance of the proposed method, we tested the system on 18 healthy subjects and compared the HRV determined by this sensor with that measured by contact-type electrocardiography (ECG). The results show a correlation of 97.43% between HRV by radar and HRV by ECG; the 95% confidence of inter-beat interval (IBI) is 59.5 ms. In addition, the proposed method was applied to monitor the change in HRV of an inpatient from Yokohama Hospital, Japan. The clinical data processing results provided consent for the nurse's daily check.\",\"PeriodicalId\":29955,\"journal\":{\"name\":\"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology\",\"volume\":\"7 4\",\"pages\":\"457-467\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10309258/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10309258/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Non-Contact Estimation of Cardiac Inter-Beat Interval and Heart Rate Variability Using Time-Frequency Domain Analysis for CW Radar
Vital signs are objective indices of health status. Heart rate variability (HRV) is the physiological phenomenon of variation in interval between consecutive heartbeats, which carries more physiological information than respiration rate (RR) or heart rate (HR). Medical radar isa potential sensor for non-contact vital sign monitoring. However, this sensor requires a more complicated process for HRV extraction. In this study, the HRV was obtained as follows: The heartbeat component was extracted from the radar signal using a locally projected noise reduction (LPNR)-based nonlinear adaptive filter and a convolution-based smoothing filter. The heartbeat component still includes undesired peaks; therefore, a derivative function was used to detect the sharpest slope peak, which is the desired peak, followed by R-peak detection to obtain HRV. To evaluate the performance of the proposed method, we tested the system on 18 healthy subjects and compared the HRV determined by this sensor with that measured by contact-type electrocardiography (ECG). The results show a correlation of 97.43% between HRV by radar and HRV by ECG; the 95% confidence of inter-beat interval (IBI) is 59.5 ms. In addition, the proposed method was applied to monitor the change in HRV of an inpatient from Yokohama Hospital, Japan. The clinical data processing results provided consent for the nurse's daily check.