{"title":"Non-Contact Calibration-Free Blood Pressure Estimation Method Using Dual Radar","authors":"Zhi Zheng, Bo Wang, Yongxin Guo","doi":"10.1109/IMBioC52515.2022.9790229","DOIUrl":null,"url":null,"abstract":"In this paper, a non-contact calibration-free blood pressure (BP) estimation method using dual radar is proposed. 13 features are extracted from the radar-captured chest pulse and wrist pulse, which will be fed into the proposed artificial neural network for the calibration-free blood pressure estimation. A non-contact database containing 27 subjects is established to enhance the robustness of the model. The results of the experiments reveal that the proposed method can perform non-contact estimation accurately and attain grade B for systolic blood pressure (SBP) estimation and almost grade A for diastolic blood pressure (DBP) estimation according to the British Hypertension Society standard.","PeriodicalId":305829,"journal":{"name":"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMBioC52515.2022.9790229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, a non-contact calibration-free blood pressure (BP) estimation method using dual radar is proposed. 13 features are extracted from the radar-captured chest pulse and wrist pulse, which will be fed into the proposed artificial neural network for the calibration-free blood pressure estimation. A non-contact database containing 27 subjects is established to enhance the robustness of the model. The results of the experiments reveal that the proposed method can perform non-contact estimation accurately and attain grade B for systolic blood pressure (SBP) estimation and almost grade A for diastolic blood pressure (DBP) estimation according to the British Hypertension Society standard.