Estimation of Forearm Motion Based on EMG Using Quaternion Neural Network
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 compute...
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| Veröffentlicht in: | Journal of advanced computational intelligence and intelligent informatics 2022-05, Vol.26 (3), p.269-278 |
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| container_title | Journal of advanced computational intelligence and intelligent informatics |
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| creator | Hashim, Hafizzuddin Firdaus Bin Ogawa, Takehiko |
| description | 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. |
| doi_str_mv | 10.20965/jaciii.2022.p0269 |
| format | Article |
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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.</description><subject>Electromyography</subject><subject>Estimation</subject><subject>Forearm</subject><subject>Human motion</subject><subject>Muscles</subject><subject>Neural networks</subject><subject>Quaternions</subject><subject>Three dimensional motion</subject><issn>1343-0130</issn><issn>1883-8014</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNotkEFPwzAMhSMEEtPYH-BUiXOH46RpcoSpG5M2EBI7R2mboo6tKUkrxL8n2zi9Z_vJlj9C7inMEZTIHvemats2FojzHlCoKzKhUrJUAuXX0TPOUqAMbskshD1A9CiA0wlZF2Foj2ZoXZe4Jlk6b40_Jlt37jybYOskmmK7Snah7T6T99EM1nen6asdvTlEGX6c_7ojN405BDv71ynZLYuPxUu6eVutF0-btGIZDCm1FecosDZlU5dKYFki1CUzJZdGyZxapiQIrDKKliOluWnyKrONsFmdC8am5OGyt_fue7Rh0Hs3-i6e1CiE4JLmSsUUXlKVdyF42-jexz_9r6agz9T0hZo-UdNnauwPUD1gkg</recordid><startdate>20220520</startdate><enddate>20220520</enddate><creator>Hashim, Hafizzuddin Firdaus Bin</creator><creator>Ogawa, Takehiko</creator><general>Fuji Technology Press Co. 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| ispartof | Journal of advanced computational intelligence and intelligent informatics, 2022-05, Vol.26 (3), p.269-278 |
| issn | 1343-0130 1883-8014 |
| language | eng |
| recordid | cdi_proquest_journals_2666481799 |
| source | DOAJ Directory of Open Access Journals |
| subjects | Electromyography Estimation Forearm Human motion Muscles Neural networks Quaternions Three dimensional motion |
| title | Estimation of Forearm Motion Based on EMG Using Quaternion Neural Network |
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