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Special Section Technical Briefs

Performance Evaluation of Heartbeat Classification Methods Based on Morphological Descriptors1

[+] Author and Article Information
Ali Haider, Kouhyar Tavakolian, Reza Fazel-Rezai

Department of Electrical Engineering,
University of North Dakota,
Grand Forks, ND 58202

Accepted and presented at The Design of Medical Devices Conference (DMD2015), April 13-16, 2015, Minneapolis, MN, USA.

Manuscript received March 3, 2015; final manuscript received March 16, 2015; published online April 24, 2015. Editor: Arthur Erdman.

J. Med. Devices 9(2), 020913 (Jun 01, 2015) (2 pages) Paper No: MED-15-1048; doi: 10.1115/1.4030120 History: Received March 03, 2015; Revised March 16, 2015; Online April 24, 2015

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References

Lin, W. H., Heye Zhang, H., and Yuan-Ting Zhang, Y. T., 2013, “Investigation on Cardiovascular Risk Prediction Using Physiological Parameters,” Comput. Math. Methods Med., 2013, p. 272691. [CrossRef] [PubMed]
Mark, R., and Moody, G., 1988, MIT-BIH Arrhythmia Database Directory, Massachusetts Institute of Technology, Cambridge, MA.
Chazal, P., and Reilly, R., 2006, “A Patient-Adapting Heartbeat Classifier Using ECG Morphology and Heartbeat Interval Features,” IEEE Trans. Biomed. Eng., 53(12), pp. 2535–2543. [CrossRef] [PubMed]
Badr, A., 1993, “A Computer Environment for ECG Waveforms Morphological Classification,” Ph.D. thesis, Rijksuniversiteit Te Gent, Gent, Belgium.
Chazal, P., O'Dwyer, M., and Reilly, R., 2004, “Automatic Classification of Heartbeats Using ECG Morphology and Heartbeat Interval Features,” IEEE Trans. Biomed. Eng., 51(7), pp. 1196–1206. [CrossRef] [PubMed]
Moody, G. B., Mark, R. G., and Goldberger, A. L., 2001, “PhysioNet: A Web-Based Resource for Study of Physiologic Signals,” IEEE Eng. Med. Biol. Mag., 20(3), pp. 70–75. [CrossRef] [PubMed]
Lee, J., Park, K. L., Song, M. H., and Lee, K. J., 2005, “Arrhythmia Classification With Reduced Features by Linear Discriminant Analysis,” 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS 2005), Shanghai, Jan. 17–18, pp. 1142–1144. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

ECG peaks as features. (a) Original ECG and (b) ECG R-peak detection.

Grahic Jump Location
Fig. 2

Distribution of training dataset

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