课题基金 / 基金详情

Targeted Reinnervation and Pattern-Recognition Control for Transradial Amputees

Targeted Reinnervation and Pattern-Recognition Control for Transradial Amputees
经桡动脉截肢者的有针对性的神经再生和模式识别控制
批准号:
7599641
负责人:
Todd Kuiken
金额:
$53.96万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-04-01 至 2013-03-31

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): We propose to provide a set of clinically viable tools and procedures to substantially improve the control of myoelectric prostheses by transradial amputees. This proposal includes a pattern-recognition control package based on algorithms with demonstrated efficacy, an innovative new surgical technique for patients with transradial amputation that will substantially improve their ability to control prostheses and receive sensation feedback from them, and advanced pattern-recognition tools that will lead to even more robust adaptive control. In this project we will perform a series of tests that will improve the control of transradial prostheses using pattern recognition techniques. Subjects will be allowed to take these prostheses home for a month-long trial, to observe and rectify any remaining problems. Targeted Muscle Reinnervation (TMR) will be performed on six subjects. TMR is a new surgical technique that transfers amputated nerve to spare muscle and skin. It provides new myoelectric signals allowing intuitive and simultaneous control for improved function in amputees TMR will improve the accuracy of control, the number of classes that may be robustly controlled, and potentially allow for simultaneous, independent control of the hand and wrist. TMR allows for more natural control of the prosthesis, and also provides targeted sensory feedback, in which the subject feels their amputated hand through reinnervated skin on the residual limb. These two surgical procedures will greatly improve the function of transradial prostheses. TMR subjects will also undergo a field trial. Finally, adaptive pattern recognition techniques and parallel classifier technology will be investigated. Adaptive control may be crucial to clinical robustness from day to day as the user adapts to the classifier. Parallel control will allow subjects to simultaneously control wrist and hand classes, with high accuracy. This proposal will advance several areas of science, including pattern recognition and the physiology of reinnervation. Parallel classifiers and adaptive algorithm theory will be substantially developed beyond the current state of the art, and the concept of robustness in the absence of a known class will be explored in the context of electromyographic signals. This proposal will also advance our understanding of motor control as we implement these novel control techniques, and provide support for future experiments which will further develop our understanding in both motor and sensory reinnervation. An outstanding team has been assembled including the Rehabilitation Institute of Chicago, the University of New Brunswick, and Otto Bock, Inc. We believe the proposed research will advance the standard of care of persons with amputation. It will also serve as an important research platform for continuing to improve artificial limb function. PUBLIC HEALTH RELEVANCE. This project will apply an innovative surgery technique to subjects with transradial amputation, to improve control of their prosthesis. It will also develop new technologies to advance the control of prostheses that have more functions including wrist rotation, wrist flexion/extension and hands with moving fingers and thumbs. These studies will significantly improve the function of artificial arms for people with below elbow amputations.
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Acquisition of Advanced Polyjet Multimaterial 3D Printer
Application of Targeted Reinnervation for People with Transradial Amputation
Application of Targeted Reinnervation for People with Transradial Amputation
Targeted Reinnervation and Pattern-Recognition Control for Transradial Amputees
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