None of the nine QRS detection algorithms detected all QRS complexes without false positives at the highest noise level, though amplitude/slope algorithms performed best for EMG noise.
The noise sensitivities for nine different QRS detection algorithms were measured for a normal, single-channel lead II, synthesized ECG corrupted with five different types of synthesized noise. The noise types were electromyographic interference, 60 Hz powerline interference, baseline drift due to respiration, abrupt baseline shift, and a composite noise constructed from all of the other noise types. The percentage of QRS complexes detected, the number of false positives, and the detection delay were measured. None of the algorithms were able to detect all QRS complexes without any false positives for all of the noise types at the highest noise level. Algorithms based on amplitude and slope had the highest performance for EMG-corrupted ECG. An algorithm using a digital filter had the best performance for the composite noise corrupted data.
Friesen et al. (Mon,) conducted a other in ECG noise sensitivity. Nine QRS detection algorithms vs. Each other was evaluated on Percentage of QRS complexes detected, number of false positives, and detection delay. None of the nine QRS detection algorithms detected all QRS complexes without false positives at the highest noise level, though amplitude/slope algorithms performed best for EMG noise.