3 Citations (Scopus)

Abstract

The automatic classification of different heart diseases for monitoring cardiac health through the use of dynamic modeling of electrocardiogram (ECG) signals would yield innovative findings of immense clinical importance. This has been a difficult problem, however, as ECG signals consist of fiducial points with different morphologies within a single heart beat; the points vary between persons and disease states and cannot be described by a single representation. Current statistical ECG models depend on user-specified parameters and a priori information that requires pre-processing. In this paper, we propose a novel method for dynamically modeling, estimating and classifying ECG signals by representing different heart diseases using the interacting multiple model (IMM) algorithm, which can adaptively choose between different representations depending on the ECG data morphology. Using real ECG signals, we demonstrate that the IMM-based model can accurately represent different morphologies with minimal prior information. Using the estimated model parameters as a low-dimensional feature set, we also showed high classification performance between different cardiac arrhythmias.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
Pages471-475
Number of pages5
DOIs
StatePublished - 2011
Event45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA, United States
Duration: Nov 6 2011Nov 9 2011

Other

Other45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
CountryUnited States
CityPacific Grove, CA
Period11/6/1111/9/11

Fingerprint

Electrocardiography
Health
Monitoring
Processing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Cite this

Edla, S., Kovvali, N., & Papandreou-Suppappola, A. (2011). Electrocardiogram signal modeling using interacting multiple models. In Conference Record - Asilomar Conference on Signals, Systems and Computers (pp. 471-475). [6190044] https://doi.org/10.1109/ACSSC.2011.6190044

Electrocardiogram signal modeling using interacting multiple models. / Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia.

Conference Record - Asilomar Conference on Signals, Systems and Computers. 2011. p. 471-475 6190044.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Edla, S, Kovvali, N & Papandreou-Suppappola, A 2011, Electrocardiogram signal modeling using interacting multiple models. in Conference Record - Asilomar Conference on Signals, Systems and Computers., 6190044, pp. 471-475, 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011, Pacific Grove, CA, United States, 11/6/11. https://doi.org/10.1109/ACSSC.2011.6190044
Edla S, Kovvali N, Papandreou-Suppappola A. Electrocardiogram signal modeling using interacting multiple models. In Conference Record - Asilomar Conference on Signals, Systems and Computers. 2011. p. 471-475. 6190044 https://doi.org/10.1109/ACSSC.2011.6190044
Edla, Shwetha ; Kovvali, Narayan ; Papandreou-Suppappola, Antonia. / Electrocardiogram signal modeling using interacting multiple models. Conference Record - Asilomar Conference on Signals, Systems and Computers. 2011. pp. 471-475
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