Affiliations: Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, North Macedonia
Correspondence:
[*]
Corresponding author: Ervin Domazet, Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, North Macedonia. E-mail: ervin_domazet@hotmail.com.
Abstract: We analyzed several QRS detection algorithms in order to build a quality industrial beat detector, intended for a small, wearable, one channel electrocardiogram sensor with a sampling rate of 125 Hz, and analog-to-digital conversion of 10 bits. The research was a lengthy process that included building several hundred rules to cope with the QRS detection problems and finding an optimal threshold value for several parameters. We obtained 99.90% QRS sensitivity and 99.90% QRS positive predictive rate measured on the first channel of rescaled and resampled MIT-BIH Arrhythmia ECG database. Even more so, our solution works better than the algorithms for the original signals with a sampling rate of 360 Hz and analog-to-digital conversion of 11 bits.
