A Review on the Applications of Time-Frequency Methods in ECG Analysis. (1st February 2023)

• Record Type: Journal Article
• Authors: Pradhan, Bikash K.; Neelappu, Bala Chakravarty; Sivaraman, J.; Kim, Doman; Pal, Kunal
• Other Names: Liu Aiping Academic Editor.
• Is Part Of: Journal of healthcare engineering. Volume 2023(2023)
• Publication Date: 2023-02-01
• Subjects: Hospital buildings -- Environmental engineering -- Periodicals; Medical technology -- Periodicals; Medical informatics -- Periodicals; 610.28
• DOI: 10.1155/2023/3145483
• Languages: English
• ISSNs: 2040-2295

Abstract

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.