Key result
A one-class support vector machine successfully detected various forms of contamination in electromyography signals, identifying contamination even when not visually discernible.
Population
Simulated and real electromyography (EMG) signals
Authors
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May aid automated EMG quality control in labs and clinics; leaves open prospective clinical validation.
A one-class SVM trained on clean EMG signals provides a generic and effective approach for detecting various forms of signal contamination, sometimes even when not visually discernible.
Fraser et al. (2014) studied Electromyography (EMG) signal contamination. One-class support vector machine (SVM) was evaluated on Detection of contaminated EMG signals. A one-class support vector machine successfully detected various forms of contamination in electromyography signals, identifying contamination even when not visually discernible.
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