Research on intelligent algorithm for detecting ECG R waves

TLDR: An intelligent algorithm of R wave detection is proposed that uses filter, multi-order difference and Shannon energy transformation to process ECG signals, and then it adopts an improved adaptive threshold method for detecting R waves.

Abstract: Waveform detection is the basis for automatic analysis of ECG signals, and the detection accuracy has an important effect on the assay performance In a cardiac cycle, R wave characteristics are very obvious and easy to identify, so most researchers take ECG R wave detection as the foundation of feature extraction This paper studies the principle of ECG R wave detection and carries out an in-depth discussion on some key technologies As a result, an intelligent algorithm of R wave detection is proposed The algorithm uses filter, multi-order difference and Shannon energy transformation to process ECG signals, and then it adopts an improved adaptive threshold method for detecting R waves The author used ECG data files from the MIT-BIH arrhythmia database (mitdb) to measure the performance of the algorithm Overall, the experiment obtained 9984% sensitivity and 9992% precision of R wave detection, while the error rate is only 024% Experiments show that, this algorithm could be also applied for R wave real-time detection under the requirements of high accuracy and low error rate