Cardiac Arrhythmias Classification and Compression using a Hybrid Technique

Asiya Al-Busaidi, Lazhar Khriji, Abdulnasir Y. Hossen


This research work discusses the challenges and limitations of real-time analysis methods of low-powered wireless sensor networks for health monitoring. The work focuses on compression of ECG signal and classification of cardiac arrhythmias. Since, the discrimination of cardiac arrhythmia is still an open research field and many classification techniques have not been tested on ECG signals yet, more investigation on hybrid classification method will be conducted. The hybrid compression and classification techniques showed promising performance compared to the classical techniques. The main significant contribution of this work is to integrate the compression and classification algorithms with less number of steps to reduce the computational load and complexity of the system. Initial prospective is to apply compression on the decomposed coefficients and then after decompressing those coefficients, features are extracted from them and used for classification.


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Paper Citation

in Harvard Style

Al-Busaidi A., Khriji L. and Y. Hossen A. (2015). Cardiac Arrhythmias Classification and Compression using a Hybrid Technique . In Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015) ISBN , pages 14-24

in Bibtex Style

author={Asiya Al-Busaidi and Lazhar Khriji and Abdulnasir Y. Hossen},
title={Cardiac Arrhythmias Classification and Compression using a Hybrid Technique},
booktitle={Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)},

in EndNote Style

JO - Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)
TI - Cardiac Arrhythmias Classification and Compression using a Hybrid Technique
SN -
AU - Al-Busaidi A.
AU - Khriji L.
AU - Y. Hossen A.
PY - 2015
SP - 14
EP - 24
DO -