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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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| 出版年: | Technol Health Care |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
IOS Press
2019
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| 主題: | |
| オンライン･アクセス: | 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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