The proposed R-peak detection algorithm using double difference and RR interval processing achieved a high detection sensitivity of 99.8% on 12-lead ECG data from the PTB diagnostic database.
Does the proposed R-peak detection algorithm accurately detect R-peaks in ECG data?
The proposed algorithm offers a highly sensitive (99.8%) and computationally simple method for automatic R-peak detection in ECG data.
The paper proposes a simple algorithm for automatic detection of the R-peaks from a single lead digital ECG data. The squared double difference signal of the ECG data is used to localise the QRS regions. The proposed method consists of three stages: sorting and thresholding of the squared double difference signal of the ECG data to locate the pproximate QRS regions, relative magnitude comparison in the QRS regions to detect the approximate R-peaks and RR interval processing to ensure accurate detection of peaks. The performance of the algorithm is tested on 12-lead ECG data from the PTB diagnostic ECG database, and a high detection sensitivity of 99.8% with low computational complexity and low sensitivity to low frequ ency noises is detected.
Sadhukhan et al. (Sun,) conducted a other in ECG data. R-peak detection algorithm using double difference and RR interval processing was evaluated on Detection sensitivity. The proposed R-peak detection algorithm using double difference and RR interval processing achieved a high detection sensitivity of 99.8% on 12-lead ECG data from the PTB diagnostic database.