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On the trade-of of accuracy and computational complexity for classifying normal and abnormal ECG in remote CVD monitoring systems

On the trade-of of accuracy and computational complexity for classifying normal and abnormal ECG in remote CVD monitoring systems
On the trade-of of accuracy and computational complexity for classifying normal and abnormal ECG in remote CVD monitoring systems
Remote cardiovascular disease monitoring systems are characterised from a limited number of available leads and limited processing capabilities. In this paper, we investigate the trade-off between accuracy and computational complexity in order to derive the best strategy for classifying the ECG signal into normal or abnormal in such systems, with the spectral energy contained in the constituent waves of the ECG signal, as the primary feature for classification. Five established classifiers are considered and through exhaustive simulations the maximum accuracy is derived for each classifier. Based on 104 ECG records, we present a systematic analysis of the tradeoff between computational complexity and accuracy, which allow us to deduce the best classification strategy considering only a small number of available leads
978-1-4673-2986-6
37-42
Chen, Taihai
62b1db38-757b-4250-8b48-de4e47f09d9e
Mazomenos, Evangelos B.
23983827-c7e7-4ee1-bfc8-986aa3594279
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Dasmahapatra, Srinandan
eb5fd76f-4335-4ae9-a88a-20b9e2b3f698
Mahesan, Niranjan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Chen, Taihai
62b1db38-757b-4250-8b48-de4e47f09d9e
Mazomenos, Evangelos B.
23983827-c7e7-4ee1-bfc8-986aa3594279
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Dasmahapatra, Srinandan
eb5fd76f-4335-4ae9-a88a-20b9e2b3f698
Mahesan, Niranjan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f

Chen, Taihai, Mazomenos, Evangelos B., Maharatna, Koushik, Dasmahapatra, Srinandan and Mahesan, Niranjan (2012) On the trade-of of accuracy and computational complexity for classifying normal and abnormal ECG in remote CVD monitoring systems At IEEE Workshop on Signal Processing Systems, Canada. 17 - 19 Oct 2012. 6 pp, pp. 37-42.

Record type: Conference or Workshop Item (Other)

Abstract

Remote cardiovascular disease monitoring systems are characterised from a limited number of available leads and limited processing capabilities. In this paper, we investigate the trade-off between accuracy and computational complexity in order to derive the best strategy for classifying the ECG signal into normal or abnormal in such systems, with the spectral energy contained in the constituent waves of the ECG signal, as the primary feature for classification. Five established classifiers are considered and through exhaustive simulations the maximum accuracy is derived for each classifier. Based on 104 ECG records, we present a systematic analysis of the tradeoff between computational complexity and accuracy, which allow us to deduce the best classification strategy considering only a small number of available leads

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More information

Submitted date: April 2012
Published date: October 2012
Venue - Dates: IEEE Workshop on Signal Processing Systems, Canada, 2012-10-17 - 2012-10-19
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 344329
URI: http://eprints.soton.ac.uk/id/eprint/344329
ISBN: 978-1-4673-2986-6
PURE UUID: 9a1e98e9-ba13-4303-880b-7e9952efc1aa

Catalogue record

Date deposited: 18 Oct 2012 11:15
Last modified: 11 Nov 2017 01:02

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Contributors

Author: Taihai Chen
Author: Evangelos B. Mazomenos

University divisions

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