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sEMG-angle estimation using feature engineering techniques for least square support vector machine
In the practical implementation of control of electromyography (sEMG) driven devices, algorithms should recognize the human’s motion from sEMG with fast speed and high accuracy. This study proposes two feature engineering (FE) techniques, namely, feature-vector resampling and time-lag techniques, to...
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| Veröffentlicht in: | Technol Health Care |
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| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
IOS Press
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6598017/ https://ncbi.nlm.nih.gov/pubmed/31045525 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3233/THC-199005 |
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