Estimation of Forearm Motion Based on EMG Using Quaternion Neural Network
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- Hashim Hafizzuddin Firdaus Bin
- Graduate School of Engineering, Takushoku University
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- Ogawa Takehiko
- Graduate School of Engineering, Takushoku University
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Abstract
<p>Quaternions are useful for representing data in three-dimensional space, and the quaternion neural network is effective for learning data in this context. On the other hand, estimating biological motion based on myopotential can be performed directly using electromyogram (EMG) signals as the computer interface. The trajectory of human forearm movement within the three-dimensional space can provide important information. In this study, the relationship between the myopotential of the upper arm muscles and the forearm motion was estimated and investigated using a quaternion neural network.</p>
Journal
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- Journal of Advanced Computational Intelligence and Intelligent Informatics
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Journal of Advanced Computational Intelligence and Intelligent Informatics 26 (3), 269-278, 2022-05-20
Fuji Technology Press Ltd.
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Details 詳細情報について
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- CRID
- 1390855068410926208
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- NII Book ID
- AA12042502
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- ISSN
- 18838014
- 13430130
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- NDL BIB ID
- 032157689
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
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- Abstract License Flag
- Disallowed