2000 Fiscal Year Final Research Report Summary
A Basic Study on Development of Intelligent Motorized Prosthetics
| Project/Area Number |
10838004
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
リハビリテーション科学
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| Research Institution | HOKKAIDO UNIVERSITY |
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Principal Investigator |
YOKOI Hiroshi HOKKAIDO Univ., Grad.School of Eng.Asso.Prof., 大学院・工学研究科, 助教授 (90271634)
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| Project Period (FY) |
1998 – 2000
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| Keywords | Adaptive Learning Theory / Processing Dura Mater Signals / Adaptability for Individuals / Achieve lost Motor Function / Multi-site Electrode / FPGA / Electrophysiology / Control of Motorized Prosthetics |
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| Research Abstract |
This research project is focused on the technical back-up for the people with spinal cord injuries to achieve the motor function, which was lost by an accident. The aim of this research is to develop a methodology on the adaptive control of the motorized prosthetics for individuals using a current LSI technology and an adaptive learning theory in order to measure and process the action potential signal of the dura mater of the spinal cord at the brain-side from the damaged area. The important components of this research are development of an adaptive classification method, reconstruction of a control function using FPGA (Filed Programmable Gate Array), classification of electrophysiological signals of a rat cranial dura mater for a new communication and control, and development of multi-site electrode using micromachining technology.
The findings achieved by this research are as follows.
1. We applied the adaptive learning theory to classify the human electromyogram as the signal includi
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ng the differences of individuals, and performed to control the prosthetic hands. As a result, the adaptation for individuals and stable classification was verified, and the adaptive learning theory was effective.
2. We measured from cranial dura mater, which is closer to the sensory cortex, in an anaesthetized rat electrophysiologically.. The cluster corresponding to the stimuli was generated by the off-line time series analysis using the adaptive learning theory.
3. With the same method, we measured the signal from the area, which is concerned with the control of the lower limb, above the Layer-I of the motor cortex using electrodes located at cranial bone. And the result showed the possibility of classification and extraction for the signal corresponding to the movement of lower limb.
4. We developed multi-layer, multi-site implantation microelectrode. And the measurement of the signal from the dura mater of the spinal cord with the various implantation methods using wire-electrode or multi-site electrode is tried.
5. The signal processing system executable to synthesize an intended mapping function and the experience system by using FPGA was developed. The experience showed that this system has the computability to synthesize the signal processing circuit on the learning theory and the capability of the effective high speed processing in terms of parallel processing.
Conclude this research : The aim of this research is to develop the device to classify the signal for individual's characteristics of action potential as the real-time adaptive processing system. For this purpose, we performed to construct adaptive classification method for nerve signal, and showed the possibility of synthesis of the signal processing circuit on the learning theory by FPGA for real-time processing. With considering the result of animal experience, we serve as a stepping-stone to develop the intelligent motorized prosthetics by adaptive classification of signal on the dura mater of the spinal cord. And we made the result of these researches public for dissertation and so on. Less
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Research Products
(12 results)
