title: Validation of new and existing decision rules for the estimation of beat-to-beat pulse transit time.
abstract: Pulse transit time (PTT) is a pivotal marker of vascular stiffness. Because the actual PTT duration in vivo is unknown and the complicated variation in waveform may occur, the robust determination of characteristic point is still a very difficult task in the PTT estimation. Our objective is to devise a method for real-time estimation of PTT duration in pulse wave. It has an ability to reduce the interference caused by both high- and low-frequency noise. The reproducibility and performance of these methods are assessed on both artificial and clinical pulse data. Artificial data are generated to investigate the reproducibility with various signal-to-noise ratios. For all artificial data, the mean biases obtained from all methods are less than 1 ms; collectively, this newly proposed method has minimum standard deviation (SD, <1 ms). A set of data from 33 participants together with the synchronously recorded continuous blood pressure data are used to investigate the correlation coefficient (CC). The statistical analysis shows that our method has maximum values of mean CC (0.5231), sum of CCs (17.26), and median CC (0.5695) and has the minimum SD of CCs (0.1943). Overall, the test results in this study indicate that the newly developed method has advantages over traditional decision rules for the PTT measurement.
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili Nanshan, Shenzhen 518055, China ; The Key Laboratory for Health Informatics of the Chinese Academy of Sciences at Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Zhou
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili Nanshan, Shenzhen 518055, China ; The Key Laboratory for Health Informatics of the Chinese Academy of Sciences at Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
authors.forename: Rongchao
authors.initials: R
authors.lastname: Peng
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili Nanshan, Shenzhen 518055, China ; The Key Laboratory for Health Informatics of the Chinese Academy of Sciences at Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
authors.forename: Hongxia
authors.initials: H
authors.lastname: Ding
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili Nanshan, Shenzhen 518055, China ; The Key Laboratory for Health Informatics of the Chinese Academy of Sciences at Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
authors.forename: Ningling
authors.initials: N
authors.lastname: Zhang
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili Nanshan, Shenzhen 518055, China ; The Key Laboratory for Health Informatics of the Chinese Academy of Sciences at Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
authors.forename: Pan
authors.initials: P
authors.lastname: Li
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology*; D001794:Blood Pressure / Q000502:physiology*; D003198:Computer Simulation; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008875:Middle Aged; D008955:Models, Cardiovascular; D011674:Pulse; D063177:Pulse Wave Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059289:Vascular Stiffness / Q000502:physiology*
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