A cardiod based technique to identify cardiovascular diseases using mobile phones and body sensors

Sufi, F, Khalil, I and Tari, Z 2010, 'A cardiod based technique to identify cardiovascular diseases using mobile phones and body sensors', in Emilio Sacristan (ed.) 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Piscataway, New Jersey, USA, 15-17 July 2010, pp. 5500-5503.


Document type: Conference Paper
Collection: Conference Papers

Title A cardiod based technique to identify cardiovascular diseases using mobile phones and body sensors
Author(s) Sufi, F
Khalil, I
Tari, Z
Year 2010
Conference name IEEE EMBC 2010
Conference location Piscataway, New Jersey, USA
Conference dates 15-17 July 2010
Proceedings title 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Editor(s) Emilio Sacristan
Publisher IEEE Engineering in Medicine and Biology Society
Place of publication Piscataway, New Jersey, USA
Start page 5500
End page 5503
Total pages 4
Abstract To prevent the threat of Cardiovascular Disease (CVD) related deaths, the usage of mobile phone based computational platforms, body sensors and wireless communications is proliferating. Since mobile phones have limited computational resources, existing PC based complex CVD detection algorithms are often unsuitable for wireless telecardiology applications. Moreover, if the existing Electrocardiography (ECG) based CVD detection algorithms are adopted for mobile telecardiology applications, then there will be processing delays due to the computational complexities of the existing algorithms. However, for a CVD affected patient, seconds worth of delay could be fatal, since cardiovascular cell damage is a totally irrecoverable process. This paper proposes a fast and efficient mechanism of CVD detection from ECG signal. Unlike the existing ECG based CVD diagnosis systems that detect CVD anomalies from hundreds of sample points, the proposed mechanism identifies cardiac abnormality from only 5 sample points. Therefore, according to our experiments the proposed mechanism is up to 3 times faster than the existing techniques. Due to less computational burden, the proposed mechanism is ideal for wireless telecardiology applications running on mobile phones.
Subjects Mobile Technologies
Networking and Communications
Keyword(s) Cardiovascular disease
Cell damage
Computational burden
Computational platforms
Computational resources
CVD diagnosis
Detection algorithm
ECG signals
PC-based
Processing delay
Sample point
Telecardiology
Wireless communications
DOI - identifier 10.1109/IEMBS.2010.5626578
Copyright notice © 2010 IEEE
ISBN 9781424441242
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