Key result
Wavelet-based QRS detection effectively suppresses ventilation and motion artifacts in ECG modeling.
Why the study?
A specialized measuring system and controllable ECG signal simulation model were needed to test and improve QRS detection algorithms.
Population
Simulated and real ECG signals
Comparison
QRS detection algorithm based on discrete wavelet transform vs uncontrolled signals
Design
Development and testing of PC-based virtual instrument with signal simulation
Authors
Loading...
Should not yet alter clinical QRS detection; leaves open validation of DWT algorithms in patient ECG recordings.
A novel PC-based virtual instrument and QRS detection algorithm using discrete wavelet transform effectively reduces noise and accurately detects QRS complexes in ECG signals.
Jóśko et al. (2005) studied Electrocardiography (ECG) signal analysis. QRS detection algorithm based on discrete wavelet transform was evaluated on Detection of QRS complexes and reduction of ventilation artifacts and motion noise. A QRS detection algorithm using discrete wavelet transform demonstrated good accuracy in reducing ventilation artifacts and motion noise when tested with a controllable ECG signal model.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: