@conference { ISI:000234856700033,
	title = {Arrhythmia classification using local Holder exponents and support vector machine},
	booktitle = {1st International Conference on Pattern Recognition and Machine Intelligence},
	series = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {3776},
	year = {2005},
	note = {1st International Conference on Pattern Recognition and Machine Intelligence, Statist Inst Kolkata, Kolkata, INDIA, DEC 20-22, 2005},
	month = {DEC},
	pages = {242-247},
	publisher = {Springer-Verlag Berlin, Heidelberger Platz 3, D-14197 Berlin, Germany},
	organization = {Springer-Verlag Berlin, Heidelberger Platz 3, D-14197 Berlin, Germany},
	address = { Statist Inst. Kolkata, India},
	abstract = {<p>We propose a novel hybrid Holder-SVM detection algorithm for arrhythmia classification. The Holder exponents are computed efficiently using the wavelet transform modulus maxima (WTMM) method. The hybrid system performance is evaluated using the benchmark MIT-BIH arrhythmia database. The implemented model classifies 160 of Normal sinus rhythm, 25 of Ventricular bigeminy, 155 of Atrial fibrillation and 146 of Nodal (A-V junctional) rhythm with 96.94\% accuracy. The distinct scaling properties of different types of heart rhythms may be of clinical importance.</p>},
	isbn = {3-540-30506-8},
	issn = {0302-9743},
	author = {Joshi, Aniruddha and Rajshekhar and Chandran, S. and Phadke, S. and Jayaraman, Valadi K. and Kulkarni, B. D.},
	editor = {Pal, S. K. and Bandyopadhyay, Sanjoy and Biswas, S.}
}
