An accurate and computationally efficient means of classifying surface myoelectric signal patterns has been the subject of considerable research effort in recent years. Effective feature extraction is crucial to reliable classification and, in the quest to improve the accuracy of transient myoelectr
β¦ LIBER β¦
Knowledge-based signal processing in the decomposition of myoelectric signals
β Scribed by Broman, H.
- Book ID
- 114561190
- Publisher
- IEEE
- Year
- 1988
- Tongue
- English
- Weight
- 555 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0739-5175
- DOI
- 10.1109/51.1970
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## Abstract In this study, we introduce a new approach to process simultaneous Electroencephalography and functional Magnetic Resonance Imaging (EEGβfMRI) data in epilepsy. The method is based on the decomposition of the EEG signal using independent component analysis (ICA) and the usage of the rel