Effect of Filtering on Pulse Wave Transit Time Measured by Photoplethysmography

Shangdi Liao, Fei Chen, Haipeng Liu, Dingchang Zheng

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review


    The waveform of a photoplethysmography (PPG) signal depends on the measurement site and individual physiological conditions. Pulse transition time (PTT) is an important physiological parameter for blood pressure estimation. PTT can be derived from electrocardiogram (ECG) and PPG waveform features. Filtering can change PPG signal waveform and the timing of PPG feature points. We aim to quantitatively investigate the filtering-induced PTT changes at different measure sites in healthy subjects of different ages. The ECG, and fingertip and earlobe PPG signals were recorded simultaneously from 58 young (age < =50) and 40 old (age > 50) healthy adults. The PPG signals were preprocessed and then filtered (low-pass, pass and stop bands: < 3 Hz and > 5Hz. The PTT difference between the preprocessed and filtered PPG signals was calculated and analyzed using analysis of variance (ANOVA) and paired tests. The results show significant effect of age and measurement site on filtering-induced PTT difference and its relative difference p < 0.05 for all). We conclude that the physiological factor including measurement site and age should be considered in PTT-based blood pressure estimation methods.

    Original languageEnglish
    Title of host publication2022 Computing in Cardiology, CinC 2022
    PublisherIEEE Computer Society
    ISBN (Electronic)9798350300970
    Publication statusE-pub ahead of print - 3 Apr 2023
    Event2022 Computing in Cardiology, CinC 2022 - Tampere, Finland
    Duration: 4 Sept 20227 Sept 2022

    Publication series

    NameComputing in Cardiology
    ISSN (Print)2325-8861
    ISSN (Electronic)2325-887X


    Conference2022 Computing in Cardiology, CinC 2022

    Bibliographical note

    Publisher Copyright:
    © 2022 Creative Commons.

    ASJC Scopus subject areas

    • Computer Science(all)
    • Cardiology and Cardiovascular Medicine


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