ABSTRACT
This paper proposed an smartphone-based real-time ECG monitoring and recognition system. The ECG signal was acquired by a MSP430FG4618 low-power microprocessor and was converted via a Bluetooth module for wireless transmission to a smartphone. A noise-tolerant ECG heartbeat recognition algorithm based on discrete wavelet transform and higher-order statistics was employed to identify different types of heartbeats. This system achieved a high accuracy of 98.34 % in identifying seven heartbeat types, which was demonstrated to outperform other studies in the literature. The heartbeat types were recognized in real-time; only 78 ms was required to identify a heartbeat. The portability, real-time processing, and high recognition rate of the system demonstrate the efficiency and effectiveness of the device as a practical computer-aided diagnosis (CAD) system.
