A new framework for classification of multi-category hand grasps using EMG signals
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Miften, FS 
ORCID: 0000-0002-3557-2194, Diykh, Mohammed ORCID: 0000-0003-0018-4199, Abdulla, Shahab ORCID: 0000-0002-1193-6969, Siuly, Siuly ORCID: 0000-0003-2491-0546, Green, Jonathan H and Deo, Ravinesh C
(2021)
A new framework for classification of multi-category hand grasps using EMG signals.
Artificial Intelligence in Medicine, 112.
ISSN 0933-3657
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/42980 |
| DOI | 10.1016/j.artmed.2020.102005 |
| Official URL | https://www.sciencedirect.com/science/article/pii/... |
| Subjects | Current > FOR (2020) Classification > 4003 Biomedical engineering Current > FOR (2020) Classification > 4201 Allied health and rehabilitation science Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | electromyogram; rehabilitation device; prosthetic hand; logarithmic spectrogram-based graph signal; AdaBoost k-means; feature selection |
| Citations in Scopus | 21 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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