Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48815
Title: Phonocardiography signal segmentation for telemedicine environments
Authors: Murillo Rendón, Santiago
Hoyos, Cristian Castro
Travieso-Gonzales, Carlos M. 
Castellanos-Domínguez, Germán
UNESCO Clasification: 3314 Tecnología médica
Keywords: Heart Sound Segmentation
Phonocardiogram
Telemedicine
Autocorrelation
Issue Date: 2013
Journal: Lecture Notes in Computer Science 
Conference: 12th International Work-Conference on Artificial Neural Networks (IWANN) 
Abstract: In this paper, phonocardiography (PCG) segmentation methodology based on envelope detection is developed by using a time-scale representation and a synthetic electrocardiogram signal (EKG). The heart cycle duration is calculated by autocorrelation of S1-S2 sounds that are synchronized with the synthetic EKG. Two algorithms for noisy signal removal are implemented to ensure the detection of signals with low signal to noise ratio. Approach is tested in a PCG database holding 232 recordings. Results show an achieved accuracy up of 90%, thus, overperforming three state-of-the-art PCG segmentation techniques used to compare the proposed approach. Additionally, the synthetic EKG is built by estimation of heart rate length, thus it does not use a patient recording EKG, reducing the computational cost and the amount of required devices.
URI: http://hdl.handle.net/10553/48815
ISBN: 9783642386817
ISSN: 0302-9743
DOI: 10.1007/978-3-642-38682-4_15
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 7903 LNCS, p. 124-134
Appears in Collections:Actas de congresos
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