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Issue title: Decision Support Systems for Medical Applications
Guest editors: D. Jude Hemanth and Valentina Emilia Balas
Article type: Research Article
Authors: Sampath, A.a; * | Sumithira, T.R.b
Affiliations: [a] Department of EEE, EBET Group of Institutions, Kangayam, Tamil nadu, India | [b] Department of EEE, K.S.R College of Engineering, Tiruchengode, Tamil nadu, India
Correspondence: [*] Corresponding author: A. Sampath, Department of EEE, EBET Group of Institutions, Kangayam, Tamil nadu, India. E-mail: [email protected]
Abstract: Electrocardiogram (ECG) is almost recurrent signals that express the activity of the heart. A large amount of information on the normal and pathological physiology of heart can be acquired from ECG. However, the ECG signals being non-stationary in nature, it is very hard to visually examine them. Thus the need is there for computer built methods for ECG signal analysis. This paper has been stimulated by the need to find an effective method for ECG signal analysis which is common and has excellent accuracy and minimum computation time. The initial task for efficient analysis is the removal of noise. It actually involves the extraction of the needed cardiac components by degeneration of the background noise. Enhancement of signal is attained by the use of multi-resolution feature extraction using DWT decomposition method. Use of this was influenced by its adaptive nature. The second task is that of P, QRS complex and T wave peak detection which is performed by the use of multi-resolution adaptive threshold method executed with DWT. The experiments are carried out on MIT-BIH database and PTB diagnostic ECG database. The results show %that our the proposed method is very effective and an efficient method for computation of P, QRS complex and T wave peak detection.
Keywords: ECG fiducial points, Discrete Wavelet Transform, multi-resolution analysis, denoising, feature extraction
DOI: 10.3233/IDT-160264
Journal: Intelligent Decision Technologies, vol. 10, no. 4, pp. 373-383, 2016
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