Authors:
Enda Barrett
1
;
Des Chambers
2
and
Cosmin Rotariu
2
Affiliations:
1
National University of Ireland Galway, Ireland
;
2
NUI Galway, Ireland
Keyword(s):
Wireless Sensor Networks, Ambulatory ECG monitoring, Arrhythmia analysis, Biomedical Signal Processing.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Physiological Computing Systems
;
Real-Time Systems
;
Wearable Sensors and Systems
Abstract:
Wireless technology has become ubiquitous in our daily lives. From 802.11 to Bluetooth we have become familiar with new technologies and expectations are rife as to its potential. The medical world is potentially lucrative for the use of such technology. The ability to improve patient comfort, monitor patients remotely and increase device mobility should all contribute handsomely to patient life quality. It also offers the unique opportunity to monitor ambulatory patients in a real-time environment. Outlined is an approach to integrate an Electrocardiogram (ECG) classifier into an overall wireless patient monitoring system enabling real-time classification and analysis of ECG data. Our research has shown that it is possible to use the open source classifier (Hamilton, 2002) in a wireless sensor network for beat detection and arrhythmia classification. We have tested the classifier with up to 80 simulated sensors proving that its lightweight implementation enables it to cope perfectly
with only minor modifications needed. It was found that the addition of multiples of sensors produced on average 0.01% performance degradation.
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