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 the prevention on the heart attack and other high risk diseases. Most of the existing devices provide ECG recording in a hospital setting or off-line ECG diagnosis. The design of a real-time wearable ECG monitoring device with cardiac arrhythmia classification system is discussed in this paper. In this system, the wearable sensor node monitors the patient´s ECG and motion signal in an unobstructive way that the patient´s daily life will not be affected. ECG analog front-end and on-node processing are designed to remove most of the noise and bias, which guarantees an clean and reliable ECG waveform. The ECG waveform is digitalized by an analog-to-digital convertor and transmitted to a smart phone via bluetooth. On the smartphone, the ECG waveform is visualized and a novel layered hidden Markov model is implemented to classify multiple cardiac arrhythmias in real time. This paper evaluates the performance of the hardware design and the classification algorithm.