Abstract: This paper presents a R wave detection algorithm based on Hilbert transform and adaptive double threshold. Firstly, amplitude normalization and Hilbert envelopment analysis are performed on the pre-processed signal. Then, the R wave is detected by the adaptive double threshold methods. Finally, the location of the detected R wave is located according to the enhanced signal. 4 kinds of databases with different frequencies and signal noise ratio,  like MIT-BIH Arrhythmia, QT, NST, European ST-T, and clinical collection of ECG data are used to evaluate the performance of the proposed algorithm. The Results show that the location of R wave in various irregular ECG signals with serious noise interference can still be accurately detected by the proposed algorithm. It has the sensitivity, positive and accuracy of the overall data detection reached 99.36%, 99.77% and 99.13% in the MIT-BIH arrhythmia database, and compared with the traditional Pan and Tompkins algorithms, the average consumption time of each record is greatly reduced, which proves that the proposed algorithm has good robustness and real-time performance.

Key words: electrocardiogram signal, R wave detection, Hilbert transform, adaptive double threshold