IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Analysis of Electrocardiogram Data Compression Techniques: A MATLAB-Based Approach

Analysis of Electrocardiogram Data Compression Techniques: A MATLAB-Based Approach
View Sample PDF
Author(s): Anukul Pandey (Dr. B. R. Ambedkar National Institute of Technology, India), Barjinder Singh Saini (Dr. B. R. Ambedkar National Institute of Technology, India), Butta Singh (Guru Nanak Dev University Regional Campus, India)and Neetu Sood (Dr. B. R. Ambedkar National Institute of Technology, India)
Copyright: 2020
Pages: 41
Source title: Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-1204-3.ch049

Purchase

View Analysis of Electrocardiogram Data Compression Techniques: A MATLAB-Based Approach on the publisher's website for pricing and purchasing information.

Abstract

In this Chapter, a MATLAB-based approach is presented for compression of Electrocardiogram (ECG) data. The methodology employs in three different domains namely direct, transformed and parameter extraction methods. The selected techniques from direct ECG compression methods are TP, AZTEC, Fan, and Cortes. Moreover selected techniques from transformed ECG compression methods are Walsh Transform, DCT, and Wavelet transform. For each of the technique, the basic implementation of the algorithm was explored, and performance measures were calculated. All 48 records of MIT-BIH arrhythmia ECG database were employed for performance evaluation of various implemented techniques. Moreover, based on requirements, any basic techniques can be selected for further innovative processing that may include the lossless encoding.

Related Content

N. Geethanjali, K. M. Ashifa, Avantika Raina, Jayashree Patil, Rameshwaran Byloppilly, S. Suman Rajest. © 2024. 19 pages.
Praveen Kakada, Muhammed Shafi M. K.. © 2024. 14 pages.
P. S. Venkateswaran, Divya Marupaka, Sachin Parate, Amit Bhanushali, Latha Thammareddi, P. Paramasivan. © 2024. 15 pages.
M. Lishmah Dominic, P. S. Venkateswaran, Latha Thamma Reddi, Sandeep Rangineni, R. Regin, S. Suman Rajest. © 2024. 15 pages.
S. Sivabala, P. Vidyasri. © 2024. 23 pages.
H. Hajra, G. Jayalakshmi. © 2024. 22 pages.
Anusha Thakur. © 2024. 15 pages.
Body Bottom