Aniruddha J. Joshi

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We propose a novel hybrid Hölder-SVM detection algorithm for arrhythmia classification. The Hölder 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(More)
Heart rate variability (HRV) provides an estimate of sympathetic and parasympathetic influences on the heart rate. Although HRV has been extensively studied, sustained clinical use is still outstanding. The noninvasive, convenient, and inexpensive arterial pulse originate from heartbeats, but has not been studied in a systematic fashion except in(More)
In this paper, we present a novel method for analysis of Ayurvedic pulse signals via a recently developed non-linear dimensionality reduction scheme called Consensus Locally Linear Embedding (C-LLE). Pulse Based Diagnosis (PBD) is a prominent method of disease detection in Ayurveda, the system of Indian traditional medicine. Ample anecdotal evidence(More)
Extensive research has been done to show that heartbeats are composed of the interaction of many physiological components operating on different time scales, with nonlinear and self-regulating nature. The more direct , and easily accessible manifestation of the heartbeat is the pulse; however, it has not been studied anywhere near as extensively. In this(More)
Previous work in biomedical signal processing area, especially in the area of cardiology indicates that most of the disorders in heart can be completely captured in an Electrocardiogram (ECG) signal and then can be classified using a classifying tool. A pulse signal (Nadi, in Ayurvedic terms) can also extract similar disorders along with the arterial(More)
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