Design of a Low-Complexity Real-Time Arrhythmia Detection System

This paper presents a low-complexity real-time arrhythmia detection system that includes the QRS complex and arrhythmia detection. The ECG data in the MIT-BIH arrhythmia database were used for simulations and verification. For QRS complex detection, this paper proposes the advanced So and Chan for detecting the R-peak and baseline of the QRS complex. Compared with the accuracy obtained using the original So and Chan method (94.61%), an accuracy of 99.29% was obtained using the advanced So and Chan method. For arrhythmia detection, the proposed system is implemented with an advanced sum of trough and various features of disease symptoms. It can identify tachycardia, bradycardia, premature contraction, and two types of cardiovascular diseases; its detection accuracy can reach 98.05%. If a morbid state occurs, a warning message will be sent to a user. Because of its low complexity, the proposed detection system can be integrated with wearable electronic devices for detecting an arrhythmia immediately.