Probabilistic Neural Network Based Delineation of QRS-complexes in Single-Lead ECG using Slope Criterion
M. K. Bhaskar1, S. S. Mehta2, N. S. Lingayat3, Guneet Singh Mehta4, D. A. Shete5

1M. K. Bhaskar, Department of Electrical Engineering, M.B.M. Engineering College, J.N.V. University, Jodhpur (Rajasthan), India.
2S.S. Mehta, Department of Electrical Engineering, M.B.M. Engineering College, J.N.V. University, Jodhpur (Rajasthan), India.
3N. S. Lingayat, Department of Electrical Engineering, Dr. B.A.T. University, I.O.P.E. Lonere (Maharashtra), India.
4Guneet Singh Mehta, Department of Electrical Engineering, Indian Institute of Technology, Jodhpur, (Rajasthan), India.
5D.A. Shete, Department of Electrical Engineering, Government Polytechnic College, Latur (Maharashtra), India.

Manuscript received on 21 July 2013 | Revised Manuscript received on 28 July 2013 | Manuscript published on 30 July 2013 | PP: 133-138 | Volume-2 Issue-3, July 2013 | Retrieval Number: C0740072313/2013©BEIESP
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Abstract: This paper presents the delineation of QRS-complexes in electrocardiogram using Probabilistic Neural Network (PNN) and Slope criteria. Before going to the step of delineation of QRS-complexes, first follow the step of detection of QRS-complexes. The results of detection rate of QRS-complexes are obtained is quite encouraging i.e. 99.23% using slope criteria and PNN. The delineation is process to determine the onset and offset of QRS-region. The delineation performance of the proposed algorithm is validated using referees annotations and the combined program median provided in the CSE multi-lead measurement library. The results of delineation are presented using BA- plots and they are found to be well within tolerance limits as specified by CSE working group.
Keywords: BA-Plot, Combined Program Median, Delineation, Probabilistic Neural Network (PNN), QRS-complexes, Refree’s Annotation.

Scope of the Article: Neural Information Processing