Juan M Padilla, Enrique J Berjano, Javier Sáiz, Rafael Rodriguez, Lorenzo Fácila
{"title":"Pulse wave velocity and digital volume pulse as indirect estimators of blood pressure: pilot study on healthy volunteers.","authors":"Juan M Padilla, Enrique J Berjano, Javier Sáiz, Rafael Rodriguez, Lorenzo Fácila","doi":"10.1007/s10558-009-9080-5","DOIUrl":null,"url":null,"abstract":"<p><p>The purpose of the study was to asses the potential use of pulse wave velocity (PWV) and digital volume pulse (DVP) as estimators of systolic (SBP) and diastolic (DPB) blood pressure. Single and multiple correlation studies were conducted, including biometric parameters and risk factors. Brachial-ankle PWV (baPWV) and DVP signals were obtained from a Pulse Trace PWV and Pulse Trace PCA (pulse contour analysis), respectively. The DVP (obtained by photoplethysmography), allowed stiffness (SI) and reflection indexes (RI) to be derived. The first study on 47 healthy volunteers showed that both SBP and DPB correlated significantly both with baPWV and SI. Multiple regression models of the baPWV and the waist-to-hip ratio (WHR) allowed SBP and DBP to be modeled with r = 0.838 and r = 0.673, respectively. SI results also employed WHR and modeled SBP and DBP with r = 0.852 and r = 0.663, respectively. RI did not correlate either with SBP or DBP. In order to avoid the use of ultrasound techniques to measure PWV, we then developed a custom-built system to measure PWV by photoplethysmography and validated it against the Pulse Trace. With the same equipment we conducted a second pilot study with ten healthy volunteers. The best SBP multiple regression model for SBP achieved r = 0.997 by considering the heart-finger PWV (hfPWV measured between R-wave and index finger), WHR and heart rate. Only WHR was significant in the DBP model. Our findings suggest that the hfPWV photoplethysmography signal could be a reliable estimator of approximate SBP and could be used, for example, to monitor cardiac patients during physical exercise sessions in cardiac rehabilitation.</p>","PeriodicalId":55275,"journal":{"name":"Cardiovascular Engineering (dordrecht, Netherlands)","volume":" ","pages":"104-12"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10558-009-9080-5","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cardiovascular Engineering (dordrecht, Netherlands)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10558-009-9080-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2009/8/6 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
The purpose of the study was to asses the potential use of pulse wave velocity (PWV) and digital volume pulse (DVP) as estimators of systolic (SBP) and diastolic (DPB) blood pressure. Single and multiple correlation studies were conducted, including biometric parameters and risk factors. Brachial-ankle PWV (baPWV) and DVP signals were obtained from a Pulse Trace PWV and Pulse Trace PCA (pulse contour analysis), respectively. The DVP (obtained by photoplethysmography), allowed stiffness (SI) and reflection indexes (RI) to be derived. The first study on 47 healthy volunteers showed that both SBP and DPB correlated significantly both with baPWV and SI. Multiple regression models of the baPWV and the waist-to-hip ratio (WHR) allowed SBP and DBP to be modeled with r = 0.838 and r = 0.673, respectively. SI results also employed WHR and modeled SBP and DBP with r = 0.852 and r = 0.663, respectively. RI did not correlate either with SBP or DBP. In order to avoid the use of ultrasound techniques to measure PWV, we then developed a custom-built system to measure PWV by photoplethysmography and validated it against the Pulse Trace. With the same equipment we conducted a second pilot study with ten healthy volunteers. The best SBP multiple regression model for SBP achieved r = 0.997 by considering the heart-finger PWV (hfPWV measured between R-wave and index finger), WHR and heart rate. Only WHR was significant in the DBP model. Our findings suggest that the hfPWV photoplethysmography signal could be a reliable estimator of approximate SBP and could be used, for example, to monitor cardiac patients during physical exercise sessions in cardiac rehabilitation.