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Blood Pressure Estimation Using a PPG Signal Recorded From the Fingertip of a Hand Moving in the Sagittal Plane

Mansourinezhad, P ; Sharif University of Technology | 2023

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  1. Type of Document: Article
  2. DOI: 10.1109/JSEN.2023.3282590
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2023
  4. Abstract:
  5. In this article, we present a new photoplethysmogram (PPG)-based blood pressure (BP) estimation approach, in which the PPG recording site (fingertip) is not in a standstill position but swings up and down in the sagittal plane during the recording. The upward and downward movements of the recording site result in useful morphological changes in the PPG signal, which can be used to better estimate BP. To investigate the effect of the vertical hand movement on the shape of the PPG signal, we first devised a PPG recording hardware and used it to collect a dataset consisting of PPG signals recorded from 120 subjects. Then, we utilized machine-learning models to estimate BP using the extracted features from the recorded PPG signals. The mean absolute and the standard deviation (STD) of the error for systolic BP (SBP) and diastolic BP (DBP) estimations were 6.63 ± 5.59 and 3.96 ± 3.82 mmHg, respectively. The results comply with the Advancement of Medical Instrumentation (AAMI) standard for BP measurement. They also achieve Grade A for diastolic and Grade B for SBP and mean BP, based on British Hypertension Society (BHS) standard. We conclude that the changes in PPG signal morphology provide more informative features resulting in more accurate BP estimation compared to using PPG signals recorded from a standstill finger. Moreover, the proposed BP estimation method has great potential for implementation in smartphones to monitor BP more accurately than the previous methods, in which the recording site is in a standstill position. © 2001-2012 IEEE
  6. Keywords:
  7. Blood pressure (BP) estimation ; Feature extraction ; Machine learning ; Moving in sagittal plane ; Photoplethysmogram (PPG)
  8. Source: IEEE Sensors Journal ; Volume 23, Issue 15 , 2023 , Pages 17751-17760 ; 1530437X (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/10147049