Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children
In this study, a one-degree-of-freedom myoelectric prosthesis system was proposed using a Parent Wireless Assistive Interface (PWAI) that allowed an external assistant (e. g., the parent of the user) to immediately adjust the parameters of the prosthetic hand controller. In the PWAI, the myoelectric...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-08-01
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| Series: | Frontiers in Neurorobotics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fnbot.2018.00048/full |
| _version_ | 1818911478870179840 |
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| author | Yutaro Hiyoshi Yuta Murai Yoshiko Yabuki Kenichi Takahana Soichiro Morishita Yinlai Jiang Yinlai Jiang Shunta Togo Shunta Togo Shinichiro Takayama Hiroshi Yokoi Hiroshi Yokoi Hiroshi Yokoi |
| author_facet | Yutaro Hiyoshi Yuta Murai Yoshiko Yabuki Kenichi Takahana Soichiro Morishita Yinlai Jiang Yinlai Jiang Shunta Togo Shunta Togo Shinichiro Takayama Hiroshi Yokoi Hiroshi Yokoi Hiroshi Yokoi |
| author_sort | Yutaro Hiyoshi |
| collection | DOAJ |
| description | In this study, a one-degree-of-freedom myoelectric prosthesis system was proposed using a Parent Wireless Assistive Interface (PWAI) that allowed an external assistant (e. g., the parent of the user) to immediately adjust the parameters of the prosthetic hand controller. In the PWAI, the myoelectric potential of use of the upper limb was plotted on an external terminal in real time. Simultaneously, the assistant adjusted the parameters of the prosthetic hand control device and manually manipulated the prosthetic hand. With these functions, children that have difficulty verbally communicating could obtain properly adjusted prosthetic hands. In addition, non-experts could easily adjust and manually manipulate the prosthesis; therefore, training for the prosthetic hands could be performed at home. Two types of hand motion discrimination methods were constructed in this study of the myoelectric control system: (1) a threshold control based on the myoelectric potential amplitude information and (2) a pattern recognition of the frequency domain features. In an evaluation test of the prosthesis threshold control system, child subjects achieved discrimination rates as high as 89%, compared with 96% achieved by adult subjects. Furthermore, the high discrimination rate was maintained by sequentially updating the threshold value. In addition, a discrimination rate of 82% on average was obtained by recognizing three motions using the pattern recognition method. |
| first_indexed | 2024-12-19T22:59:21Z |
| format | Article |
| id | doaj.art-d991bc1561d542169543882fa73fc79f |
| institution | Directory Open Access Journal |
| issn | 1662-5218 |
| language | English |
| last_indexed | 2024-12-19T22:59:21Z |
| publishDate | 2018-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurorobotics |
| spelling | doaj.art-d991bc1561d542169543882fa73fc79f2022-12-21T20:02:33ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182018-08-011210.3389/fnbot.2018.00048373427Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for ChildrenYutaro Hiyoshi0Yuta Murai1Yoshiko Yabuki2Kenichi Takahana3Soichiro Morishita4Yinlai Jiang5Yinlai Jiang6Shunta Togo7Shunta Togo8Shinichiro Takayama9Hiroshi Yokoi10Hiroshi Yokoi11Hiroshi Yokoi12Department of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanBeijing Innovation Center for Intelligent Robots and Systems, Beijing, ChinaNational Center for Child Health and Development, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanNational Center for Child Health and Development, Tokyo, JapanBrain Science Inspired Life Support Research Center, The University of Electro-Communications, Tokyo, JapanDepartment of Mechanical and Intelligent System Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, JapanBeijing Innovation Center for Intelligent Robots and Systems, Beijing, ChinaNational Center for Child Health and Development, Tokyo, JapanIn this study, a one-degree-of-freedom myoelectric prosthesis system was proposed using a Parent Wireless Assistive Interface (PWAI) that allowed an external assistant (e. g., the parent of the user) to immediately adjust the parameters of the prosthetic hand controller. In the PWAI, the myoelectric potential of use of the upper limb was plotted on an external terminal in real time. Simultaneously, the assistant adjusted the parameters of the prosthetic hand control device and manually manipulated the prosthetic hand. With these functions, children that have difficulty verbally communicating could obtain properly adjusted prosthetic hands. In addition, non-experts could easily adjust and manually manipulate the prosthesis; therefore, training for the prosthetic hands could be performed at home. Two types of hand motion discrimination methods were constructed in this study of the myoelectric control system: (1) a threshold control based on the myoelectric potential amplitude information and (2) a pattern recognition of the frequency domain features. In an evaluation test of the prosthesis threshold control system, child subjects achieved discrimination rates as high as 89%, compared with 96% achieved by adult subjects. Furthermore, the high discrimination rate was maintained by sequentially updating the threshold value. In addition, a discrimination rate of 82% on average was obtained by recognizing three motions using the pattern recognition method.https://www.frontiersin.org/article/10.3389/fnbot.2018.00048/fullmyoelectric prosthetic handEMGhuman-machine interfacechildrenartificial neural networkthreshold |
| spellingShingle | Yutaro Hiyoshi Yuta Murai Yoshiko Yabuki Kenichi Takahana Soichiro Morishita Yinlai Jiang Yinlai Jiang Shunta Togo Shunta Togo Shinichiro Takayama Hiroshi Yokoi Hiroshi Yokoi Hiroshi Yokoi Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children Frontiers in Neurorobotics myoelectric prosthetic hand EMG human-machine interface children artificial neural network threshold |
| title | Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children |
| title_full | Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children |
| title_fullStr | Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children |
| title_full_unstemmed | Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children |
| title_short | Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children |
| title_sort | development of a parent wireless assistive interface for myoelectric prosthetic hands for children |
| topic | myoelectric prosthetic hand EMG human-machine interface children artificial neural network threshold |
| url | https://www.frontiersin.org/article/10.3389/fnbot.2018.00048/full |
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