Assessing the Effects of Filtering Processing on Pulse Wave Transit Time Measured by Photoplethysmography from Earlobe

Shangdi Liao1; Haipeng Liu2; Dingchang Zheng2; Fei Chen1

10.1109/APSIPAASC58517.2023.10317481

2023-10-31

Asia-Pacific-Signal-and-Information-Processing-Association Annual Summit and Conference (APSIPA ASC)

2640-009X

979-8-3503-0068-0

2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

1417-1421

31 Oct.-3 Nov. 2023

Taipei, Taiwan

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

The waveform of a photoplethysmography (PPG) signal depends on individual physiological conditions. Pulse transition time (PTT), derived from electrocardiogram (ECG) and PPG waveform features, is an important physiological parameter for blood pressure estimation. Filtering can change PPG signal waveform and the timing of PPG feature points. This work aimed to quantitatively investigate the filtering-induced PTT changes at earlobe in healthy subjects of different ages and with different PTT definitions. The ECG and earlobe PPG signals were recorded simultaneously at a sample rate of 2500 Hz for 120 s from 100 healthy adults in 5 age groups (20-29, 30-39, 40-49, 50-59, and over 60 years). The PPG signals were preprocessed using band-pass filtering (pass and stop bands: >0.5 Hz and <0.2 Hz for high-pass filter, <20 Hz and >30 Hz for low-pass filter) and then low-pass filtered (pass and stop bands: <3 Hz and >5 Hz). The PTT difference between the preprocessed and filtered PPG signals was calculated and analyzed. Four pulse feature points were defined and extracted (i.e., maximum peak (MP), valley point (VP), maximal first derivative (M1D), and maximal second derivative (M2D)). The results showed significant effect of PTT definition on filtering-induced PTT relative difference (p<0.001). It was found that the age group (50-59) and the MP definition had the minimum filtering-induce PTT changes. This work suggested that the physiological factors including PTT definition and age should be considered in the PTT-based blood pressure estimation methods.

Band-pass filters Pulse measurements Low-pass filters Estimation Electrocardiography Photoplethysmography Feature extraction

第一

英语

EI ; CPCI-S

Shenzhen Key Technology Program Funding[JSGG20220831103803006]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods

WOS:001108741800222

20235115257192

Biomedical signal processing ; Blood ; Blood pressure ; Electrocardiography ; High pass filters ; Low pass filters ; Physiological models

Biological Materials and Tissue Engineering:461.2 ; Medicine and Pharmacology:461.6 ; Biology:461.9 ; Electricity: Basic Concepts and Phenomena:701.1 ; Electric Filters:703.2 ; Information Theory and Signal Processing:716.1

IEEE

1.Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
2.Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom

Shangdi Liao,Haipeng Liu,Dingchang Zheng,et al. Assessing the Effects of Filtering Processing on Pulse Wave Transit Time Measured by Photoplethysmography from Earlobe[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1417-1421.