Optimal DSP bandpass filtering for QRS detection

An electrocardiogram refers to the process of recording the electrical activity of the heart over a certain time interval. ECG signal holds vital information for the current health condition of the patient. Detection of cardiac disorders is based on detection of sudden deviations from the mean line. Detection of heartbeat functions is based on extracting ECG characteristic features, especially the R-peak. Although in this paper we address a general approach, we focus on using wearable ECG sensors and developing an efficient QRS detector to determine the heartbeat function. The real problem in detection and ECG signal analysis is processing the noise contaminated ECG signal and the way one can reduce the feature space to extract the relevant features. In this paper, we set a research question to investigate how the filter affects the accuracy, sensitivity and precision values on QRS detectors. We report our findings on optimal filter design with a central frequency of 8.33 Hz and −3db cutoff frequencies at 4 Hz and 20 Hz. The analysis addresses development of an efficient filter with small computing complexity intended to be used for wearable ECG sensors.