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Authors: Z. Bouguila 1 ; A. Moukadem 1 ; A. Dieterlen 1 ; A. Ahmed Benyahia 2 ; A. Hajjam 3 ; S. Talha 4 and E. Andres 4

Affiliations: 1 University of Haute Alsace, France ; 2 Université de Technologie Belfort Montbéliard and Newel, France ; 3 Université de Technologie Belfort Montbéliard, France ; 4 Hôpital Civil, France

ISBN: Not Available

Keyword(s): E-care, telemedicine, time-frequency, reassignment, synchrosqueezing, correlation

Abstract: Despite considerable advances in medical therapy, heart failure remains a substantial burden of mortality and economic cost. This is tangibly seen by the rising number of healthcare systems that are adopting telemedicine, by the development of industry investments in telemedicine products and involvement of government in project delivery. The main objective of the telemedicine E-care (www.projet-e-care.fr) project is to greatly contribute to the enhancement of the remote patient monitoring, expanding the possibilities for lifesaving care. In this project, oriented for heart failure patients with NYHA (class III) severity, a smart platform is adopted for home monitoring using noninvasive standard sensors and specific cardiac devices (ElectroCardioGram and PhonoCardioGram). This thesis contribution, with our partners, is to enhance the signal processing part for accurate diagnostic. Although ECG and PCG signals play important roles in heart abnormality detection, diagnosis based on th is signal individually cannot detect most cases of heart symptoms, like detection of S4 pathological heart sound. Previously in our laboratory, time-frequency methods showed here potential on PCG segmentation and classification; however these methods can suffer from poor energy concentration in time frequency domain. Hence the first theoretical thesis objective is to optimize the energy concentration of Stockwell time-frequency transform. The second objective, based on the first results, is to combine by time-frequency correlation the information contained in PCG and ECG. This original approach will help us extracting features to classify accurately heart disease. All these methods should be validated by an experimented cardiologist during a measure campaign in Strasbourg University Hospital. (More)

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Paper citation in several formats:
Bouguila, Z.; Moukadem, A.; Dieterlen, A.; Ahmed Benyahia, A.; Hajjam, A.; Talha, S. and Andres, E. (2014). Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal.In Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014) ISBN Not Available, pages 36-40

author={Z. Bouguila. and A. Moukadem. and A. Dieterlen. and A. Ahmed Benyahia. and A. Hajjam. and S. Talha. and E. Andres.},
title={Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal},
booktitle={Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014)},
isbn={Not Available},


JO - Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014)
TI - Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal
SN - Not Available
AU - Bouguila, Z.
AU - Moukadem, A.
AU - Dieterlen, A.
AU - Ahmed Benyahia, A.
AU - Hajjam, A.
AU - Talha, S.
AU - Andres, E.
PY - 2014
SP - 36
EP - 40
DO -

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