Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm
In recent years, many myoelectric arms that are controlled based on electromyogram (EMG) signals of amputee's stump or residual muscles have been proposed. In the cases of above elbow amputees, however, the muscles which generate the forearm, wrist and hand motions do not remain. Therefore,...
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| Format: | Article |
| Language: | English |
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The Japan Society of Mechanical Engineers
2013-02-01
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| Series: | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/jamdsm/7/1/7_74/_pdf/-char/en |
| _version_ | 1818107830482239488 |
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| author | Kazuo KIGUCHI Thilina Dulantha LALITHARATNE Yoshiaki HAYASHI |
| author_facet | Kazuo KIGUCHI Thilina Dulantha LALITHARATNE Yoshiaki HAYASHI |
| author_sort | Kazuo KIGUCHI |
| collection | DOAJ |
| description | In recent years, many myoelectric arms that are controlled based on electromyogram (EMG) signals of amputee's stump or residual muscles have been proposed. In the cases of above elbow amputees, however, the muscles which generate the forearm, wrist and hand motions do not remain. Therefore, most myoelectric arms for above elbow amputees have less degree of freedom and its dexterity is relatively poor compared with a human upper-limb. To improve the quality of life of above elbow amputees and to increase their mobility in daily life activities, some additional input signals must be prepared. One of the strong candidates of the additional input signals is an electroencephalogram (EEG) signal. An EEG signal is an electric signal that can be measured along a scalp, so that it can be measured even with an above elbow amputee. In this study, an artificial arm for above elbow amputees is controlled based on EMG and EEG signals. In this paper, the EEG-based motion estimation method is proposed to control the forearm supination/pronation motion of the artificial arm. The angle, angular velocity, and angular acceleration of the forearm motion are estimated under several velocities by using EEG signals. |
| first_indexed | 2024-12-11T02:05:42Z |
| format | Article |
| id | doaj.art-bd8e815039404fc4a266a60ef16f6af2 |
| institution | Directory Open Access Journal |
| issn | 1881-3054 |
| language | English |
| last_indexed | 2024-12-11T02:05:42Z |
| publishDate | 2013-02-01 |
| publisher | The Japan Society of Mechanical Engineers |
| record_format | Article |
| series | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| spelling | doaj.art-bd8e815039404fc4a266a60ef16f6af22022-12-22T01:24:23ZengThe Japan Society of Mechanical EngineersJournal of Advanced Mechanical Design, Systems, and Manufacturing1881-30542013-02-0171748110.1299/jamdsm.7.74jamdsmEstimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial ArmKazuo KIGUCHI0Thilina Dulantha LALITHARATNE1Yoshiaki HAYASHI2Department of Mechanical Engineering, Kyushu UniversityDepartment of Advanced Technology Fusion, Saga UniversityDepartment of Advanced Technology Fusion, Saga UniversityIn recent years, many myoelectric arms that are controlled based on electromyogram (EMG) signals of amputee's stump or residual muscles have been proposed. In the cases of above elbow amputees, however, the muscles which generate the forearm, wrist and hand motions do not remain. Therefore, most myoelectric arms for above elbow amputees have less degree of freedom and its dexterity is relatively poor compared with a human upper-limb. To improve the quality of life of above elbow amputees and to increase their mobility in daily life activities, some additional input signals must be prepared. One of the strong candidates of the additional input signals is an electroencephalogram (EEG) signal. An EEG signal is an electric signal that can be measured along a scalp, so that it can be measured even with an above elbow amputee. In this study, an artificial arm for above elbow amputees is controlled based on EMG and EEG signals. In this paper, the EEG-based motion estimation method is proposed to control the forearm supination/pronation motion of the artificial arm. The angle, angular velocity, and angular acceleration of the forearm motion are estimated under several velocities by using EEG signals.https://www.jstage.jst.go.jp/article/jamdsm/7/1/7_74/_pdf/-char/enartificial armeeg signalmotion estimation |
| spellingShingle | Kazuo KIGUCHI Thilina Dulantha LALITHARATNE Yoshiaki HAYASHI Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm Journal of Advanced Mechanical Design, Systems, and Manufacturing artificial arm eeg signal motion estimation |
| title | Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm |
| title_full | Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm |
| title_fullStr | Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm |
| title_full_unstemmed | Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm |
| title_short | Estimation of Forearm Supination/Pronation Motion Based on EEG Signals to Control an Artificial Arm |
| title_sort | estimation of forearm supination pronation motion based on eeg signals to control an artificial arm |
| topic | artificial arm eeg signal motion estimation |
| url | https://www.jstage.jst.go.jp/article/jamdsm/7/1/7_74/_pdf/-char/en |
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