A Real-Time Cardiac Arrhythmia Classification System with Wearable Electrocardiogram

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. A design of a real-time wearable ECG monitoring system with cardiac arrhythmia classification is proposed in this pap...

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Bibliographic Details
Published in2011 International Conference on Body Sensor Networks pp. 119 - 124
Main Authors Sheng Hu, Zhenzhou Shao, Jindong Tan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Accelerometers
Biomedical monitoring
Cardiac Arrhythmia Classification
Electrocardiography
Hidden Markov models
Leg
LHMM
Noise
Real time systems
Wearabl ECG
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Summary:Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. A design of a real-time wearable ECG monitoring system with cardiac arrhythmia classification is proposed in this paper. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Last, human activities by an accelerometer can be identified to reduce the chance of false alarm in classification due to the motion artifacts.
ISBN:1457704692
9781457704697
ISSN:2376-8886
DOI:10.1109/BSN.2011.17