2019
DOI: 10.35940/ijitee.i1137.0789s19
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Detection of Congestive Heart Failure Based on Spectral Features and Extreme Learning Machine

Abstract: In this paper we proposed a novel approach to evaluate the classification performance of features derived from various spectral investigation methods for congestive Heart Failure (CHF) analysis using ranking methods, Kernel Principal Component Analysis (KPCA) and binary classifier as 1-norm linear programming extreme learning machine (1-NLPELM). For this study, thirty different features are extracted from heart rate variability (HRV) signal by using spectral methods like multiscale Wavelet packet (MSWP), highe… Show more

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References 31 publications
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