A Review on the Applications of Time-Frequency Methods in ECG Analysis

Author:

Pradhan Bikash K.1ORCID,Neelappu Bala Chakravarty1ORCID,Sivaraman J.1ORCID,Kim Doman23ORCID,Pal Kunal1ORCID

Affiliation:

1. Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, Rourkela 769008, India

2. Graduate School of International Agricultural Technology, Seoul National University, Pyeongchang-gun, Gangwon-do 25354, Republic of Korea

3. Institute of Food Industrialization, Institutes of Green Bioscience and Technology, Seoul National University, Pyeongchang-gun, Gangwon-do 25354, Republic of Korea

Abstract

The joint time-frequency analysis method represents a signal in both time and frequency. Thus, it provides more information compared to other one-dimensional methods. Several researchers recently used time-frequency methods such as the wavelet transform, short-time Fourier transform, empirical mode decomposition and reported impressive results in various electrophysiological studies. The current review provides comprehensive knowledge about different time-frequency methods and their applications in various ECG-based analyses. Typical applications include ECG signal denoising, arrhythmia detection, sleep apnea detection, biometric identification, emotion detection, and driver drowsiness detection. The paper also discusses the limitations of these methods. The review will form a reference for future researchers willing to conduct research in the same field.

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

Reference199 articles.

1. A neural network approach and wavelet analysis for ECG classification;M. K. Gautam

2. Detection and extraction of the ECG signal parameters;H. Gholam-Hosseini

3. A Survey on Change Detection and Time Series Analysis with Applications

4. Joint time-frequency analysis

5. Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics

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