A PD control-based QRS detection algorithm for wearable ECG applications achieved an overall sensitivity of 99.28% and a positive predictive value of 99.26%.
Does a PD control-based QRS detection algorithm accurately detect QRS waves in wearable ECG applications for patients with cardiovascular diseases?
A novel PD control-based QRS detection algorithm demonstrates high sensitivity and positive predictive value with low computational complexity, making it suitable for real-time mobile ECG monitoring.
We present a QRS detection algorithm for wearable ECG applications using a proportional-derivative (PD) control. ECG data of arrhythmia have irregular intervals and magnitudes of QRS waves that impede correct QRS detection. To resolve the problem, PD control is applied to avoid missing a small QRS wave followed from a large QRS wave and to avoid falsely detecting noise as QRS waves when an interval between two adjacent QRS waves is large (e.g. bradycardia, pause, and arioventricular block). ECG data was obtained from 78 patients with various cardiovascular diseases and tested for the performance evaluation of the proposed algorithm. The overall sensitivity and positive predictive value were 99.28% and 99.26%, respectively. The proposed algorithm has low computational complexity, so that it can be suitable to apply mobile ECG monitoring system in real time.
Choi et al. (Wed,) conducted a other in various cardiovascular diseases (n=78). PD control-based QRS detection algorithm was evaluated on QRS detection sensitivity and positive predictive value. A PD control-based QRS detection algorithm for wearable ECG applications achieved an overall sensitivity of 99.28% and a positive predictive value of 99.26%.