The Studies on the Control Method of Multifunctional Powered Prosthesis by Using Multi-channel EMG Signals.
| Project/Area Number |
60550300
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | HIROSHIMA UNIVERSITY |
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Principal Investigator |
ITO Koji Hiroshima University, Faculty of Engineering, Associate Professor,, 工学部, 助教授 (30023310)
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| Project Period (FY) |
1985 – 1986
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| Project Status |
Completed (Fiscal Year 1986)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1986: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 1985: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | Powered Prosthesis / Human-Prosthesis System / Bilinear System / EMG / AR model / 力制御 / 機能識別 / 運動制御 |
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| Research Abstract |
The final goals of prostheses research are to develop artificial limbs controlled naturally by the amputee's motor intents and responding functionally like the natural limbs. However, most prostheses in present use are still far from the goals in spite of recent advanced technologies of robot manipulators. Progress in prostheses requires a more intimates and artificial limbs, and a clearer understanding of neuro-muscular-skeletal system controlling natural limbs.
1) The Control Method of Myoelectric Powered Prostheses with Bilinear Variable Structure---- In the present study, it was shown that the neuromuscular system had a bilinear form on the basis of the visco-elastic properties and that from various experiments, the implimentation of the bilinear structure as an interface in human-prosthesis system would lead to much improvements in the amputee's control ability.
2) Limb-Function Discrimination Method Using Multichannel EMG Signals---- The discrimination method which was not dependent on the locations of the electrodes was developed using the amplitudes frequency informations, and cross correlations among multichannel EMG signals. It was realized by combining the multivariant autoregressive(AR) model with the statistical discriminant function. Then, it was shown that the success rates more than 97 % was gained for the six functions of motions of the forarm and wrist.
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Report
(1 results)
Research Products
(10 results)
