Spatial Filtering for Robust Myoelectric Control
| Autor: | Janne M. Hahne, Bernhard Graimann, Klaus-Robert Müller |
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| Rok vydání: | 2012 |
| Předmět: |
Male
Engineering Speech recognition Feature extraction Biomedical Engineering Artificial Limbs Electromyography Motor Activity Pattern Recognition Automated Robustness (computer science) medicine Humans Muscle Skeletal Spatial filter medicine.diagnostic_test business.industry Covariance matrix Reproducibility of Results Signal Processing Computer-Assisted Pattern recognition Hand Visualization Forearm Filter design Female Artificial intelligence Robust control business Algorithms |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 59:1436-1443 |
| ISSN: | 1558-2531 0018-9294 |
| Popis: | Pattern recognition techniques have been applied to extract information from electromyographic (EMG) signals that can be used to control electrical powered hand prostheses. In this paper, optimized spatial filters that enhance separation properties of EMG signals are investigated. In particular, different multiclass extensions of the common spatial patterns algorithm are applied to high-density surface EMG signals acquired from the forearms of ten healthy subjects. Visualization of the obtained filter coefficients provides insight into the physiology of the muscles related to the performed contractions. The CSP methods are compared with a commonly used pattern recognition approach in a six-class classification task. Cross-validation results show a significant improvement in performance and a higher robustness against noise than commonly used pattern recognition methods. |
| Databáze: | OpenAIRE |
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