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 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. © 2011 IEEE.
Proceedings - 2011 International Conference on Body Sensor Networks, BSN 2011
A real-time cardiac arrhythmia classification system with wearable electrocardiogram.
Proceedings - 2011 International Conference on Body Sensor Networks, BSN 2011, 119-124.
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