Design and implementation of a low-complexity R-peak detection algorithm

Cardiovascular disease, which is one of the most dangerous diseases in modern medicine, has become a threat to people's health. ECG is a kind of information that can reflect the physiological characteristics of human heart. With the development of modern technology, achieving ECG for health monitoring in the wearable hardware has become increasingly popular. The detection of R-peak is very important in ECG signal processing. This paper presents a low complexity r-peak detection algorithm, which is suitable for ASIC implementation. First of all, the algorithm use digital filter and envelope filter to remove the noise which is in the ECG. Then it use the Hilbert transform convert the r-peak to zero-crossing point. At last, it check the zero-crossing point to finish the R-peak detection. The algorithm is using the first-channel of the MIT-BIH arrhythmia database to test, and achieves average detection accuracy of 99.81%, sensitivity of 99.87%.