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Effect of adaptive motion-artifact reduction on QRS detection
P S Hamilton1, M Curley, R Aimi
1E. P. Limited, Cambridge, MA 02139, USA. pat@eplimited.com
Biomedical Instrumentation & Technology
|June 27, 2000
Summary
An adaptive algorithm effectively removed motion artifacts from electrocardiogram (ECG) recordings, significantly reducing false QRS detections by an average of 72.6% and improving signal quality for ambulatory monitoring.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Cardiology
Background:
- Motion artifact is a major noise source in physiological recordings like ECG, EEG, and EMG.
- This noise is particularly problematic in ambulatory ECG monitoring due to overlapping bandwidths with the desired signal.
Purpose of the Study:
- To evaluate the efficacy of an adaptive motion-artifact removal algorithm.
- To assess the algorithm's impact on the performance of a standard QRS detector in ECG recordings.
Main Methods:
- Four ECG recordings were obtained from three subjects, with induced motion artifact.
- An adaptive noise removal algorithm utilized a skin-stretch signal as a reference for artifact suppression.
- The algorithm's effect on QRS detection accuracy was analyzed.
Main Results:
- The adaptive noise removal algorithm reduced false QRS detections from 380 to 104.
- This represents an average reduction of 72.6% in false detections across all records.
- Individual record reductions in false detections varied from 12% to 93%.
Conclusions:
- Adaptive motion-artifact removal significantly improves the accuracy of QRS detection in ECG signals.
- This technique offers a promising solution for enhancing the reliability of ambulatory ECG monitoring.