Electrocardiogram signal processing and recognition techniques based on the ESPRIT algorithm

Qianting Zhao; Qingwei Ping

doi:10.1117/12.3036768

13 July 2024 Electrocardiogram signal processing and recognition techniques based on the ESPRIT algorithm

Qianting Zhao, Qingwei Ping

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132080Z (2024) https://doi.org/10.1117/12.3036768
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

The characteristics of electrocardiogram (ECG) signal play a crucial role in assessing human health. Accurate identification of frequency components within ECG signal can greatly assist physicians in evaluating patients' health conditions and devising appropriate treatment strategies. The process of acquiring ECG signal involves the following several stages: signal acquisition, preprocessing, feature extraction and classification. However, existing feature extraction methods have limitations, which can compromise their effectiveness for clinical applications. The ESPRIT algorithm, based on eigen decomposition of correlation matrices, offers a solution for signal feature estimation. It enables the computation of signal frequency, phase, power, and other parameters, making it particularly useful in array signal processing for precise parameter estimation even with limited data. To address these limitations, this paper proposes a novel feature analysis method based on the ESPRIT algorithm. Our goal is to overcome the shortcomings of conventional feature extraction techniques, which are often computationally intensive, require extensive calculations, and may not accurately extract electrocardiogram signal features. The proposed method was evaluated using data from the MIT-BIH database, demonstrating the ESPRIT algorithm's ability to accurately estimate frequencies. These results provide critical insights and guidance that can enhance the accuracy of ECG signal acquisition.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qianting Zhao and Qingwei Ping "Electrocardiogram signal processing and recognition techniques based on the ESPRIT algorithm", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132080Z (13 July 2024); https://doi.org/10.1117/12.3036768

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Electrocardiography

Signal processing

Tunable filters

Linear filtering

Signal to noise ratio

Electronic filtering

Signal filtering

Keywords/Phrases

Search In:

Publication Years