Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation

Overview

Journal IEEE J Transl Eng Health Med

Specialty Biomedical Engineering

Date 2020 Jun 30

PMID 32596063

Citations 2

Authors

Muskan Singla

Syed Azeemuddin

Prasad Sistla

Affiliations

Soon will be listed here.

Abstract

Objective: This paper presents feature extraction from each beat of ECG and PPG signals to make BP measurements uninterrupted. These features are extracted by employing Haar transformation to adaptively attenuate measurement noise and improve the fiducial point detection precision.

Method: the use of only PAT feature as an independent variable leads to an inaccurate estimation of either Systolic Blood Pressure (SBP) or Diastolic Blood Pressure (DBP) or both. We propose the extraction of supplementary features that are highly correlated to physiological parameters. Concurrent data was collected as per the Association for the Advancement of Medical Instrumentation (AAMI) guidelines from 171 human subjects belonging to diverse age groups. An Adaptive Window Wavelet Transformation (AWWT) technique based on Haar wavelet transformation has been introduced to segregate pulses. Further, an algorithm based on log-linear regression analysis is developed to process extracted features from each beat to calculate BP.

Results: The mean error of 0.43 and 0.20 mmHg, mean absolute error of 4.6 and 2.3 mmHg, and Standard deviation of 6.13 and 3.06 mmHg is achieved for SBP and DBP respectively.

Conclusions: The features extracted are highly precise and evaluated BP values are as per the AAMI standards. Clinical Impact: This continuous real-time BP monitoring technique can be useful in the treatment of hypertensive and potential-hypertensive subjects.

Citing Articles

Boosted-SpringDTW for Comprehensive Feature Extraction of PPG Signals.

Martinez J, Sel K, Mortazavi B, Jafari R IEEE Open J Eng Med Biol. 2022; 3:78-85.

PMID: 35873901 PMC: 9299207. DOI: 10.1109/OJEMB.2022.3174806.

Design and Implementation of a Wireless Medical Robot for Communication Within Hazardous Environments.

Maher N, Elsheikh G, Ouda A, Anis W, Emara T Wirel Pers Commun. 2021; 122(2):1391-1412.

PMID: 34462621 PMC: 8387213. DOI: 10.1007/s11277-021-08954-7.

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