NDLI: Efficient dynamic modelling of ECG with myocardial infarction using interacting multiple model and particle filter

Content Provider	IET Digital Library
Author	Swain, Sushree Satvatee Patra, Dipti
Abstract	The automatic identification of cardiac condition through dynamic modelling of electrocardiogram (ECG) signal has immense clinical significance as it eliminates the task of manual annotation of ECG recordings. In this study, an interacting multiple model (IMM)-based scheme has been proposed that helps in dynamically modelling and estimating the ECG signal. This model is having the adaptability of interchanging among several morphological representations. It offers the advantage of not necessitating user-specific parameters. This model does not necessitate a priori information about the ECG signal to initialise the filter parameters and delimitation of fiducial points of ECG signal. The particle filter (PF)-based schemes show superiority owing to their freedom from a single assumption on the signal model and noise model. Besides, it has got the potential of simultaneously tracking multiple pathological and morphological changes occurring in biomedical signals. Thus, the parameters of the model are estimated by adopting the PF, so that the myocardial infarction (MI) affected ECG signals can be efficiently tracked. Investigations on ECG signals from the MIT-BIH database and PTB diagnostic ECG database signify that the IMM-PF scheme can represent several MI morphologies with minimum prior information without distorting the helpful diagnostic information of ECG accurately.
Starting Page	495
Ending Page	505
Page Count	11
ISSN	17519675
Volume Number	14
e-ISSN	17519683
Issue Number	Issue 8, Oct (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/14/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2019.0458
Journal	IET Signal Processing
Publisher Date	2020-07-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bioelectric Signal Biology And Medical Computing Biomedical Signal Digital Signal Processing ECG Recordings Efficient Dynamic Modelling Electrical Activity in Neurophysiological Processes Electrocardiogram Signal Electrocardiography Electrodiagnostics And Other Electrical Measurement Technique Filtering Method in Signal Processing Interacting Multiple Model-based Scheme Medical Signal Processing Morphological Changes Multiple Pathological Changes Myocardial Infarction Affected ECG Signal Noise Model Particle Filter Particle Filter-based Scheme PTB Diagnostic ECG Database Signal Model
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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