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: 7446020
• 负责人: Todd Kuiken
• 金额: $ 55.83万
• 依托单位: REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7446020
• 关键词: Algorithms; Amplifiers; Amputation; Amputees; Area; Artificial Arm; Artificial limb procedure; Arts; Benchmarking; Biological; Caring; Characteristics; Chicago; Class; Classification; Clinical; Communities; Complement; Complex; Data; Development; Elbow; Electrodes; Ensure; Environment; Esthesia; Feedback; Fingers; Forearm; Foundations; Freedom; Future; Hand; Home environment; Hour; Individual; Institutes; Institution; Laboratories; Lead; Limb Prosthesis; Limb structure; Motor; Movement; Muscle; Myoelectric prosthesis; Nerve; Nerve Transfer; New Brunswick; Numbers; Operative Surgical Procedures; Patients; Pattern Recognition; Performance; Persons; Physiology; Positioning Attribute; Procedures; Process; Prosthesis; Public Health; Reaction Time; Rehabilitation therapy; Research; Residual state; Rotation; Science; Sensory; Series; Signal Transduction; Skin; Standards of Weights and Measures; System; Techniques; Technology; Testing; Thumb structure; Time; Training; Universities; Upper Extremity; Upper arm; Work; Wrist; base; clinical application; computerized data processing; concept; day; design; disability; electric impedance; evaluation/testing; experience; graphical user interface; grasp; improved; improved functioning; innovation; motor control; new technology; novel; reinnervation; relating to nervous system; research clinical testing; research study; sensory feedback; theories; tool

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.

描述（由申请人提供）：我们建议提供一套临床可行的工具和程序，以大大改善经桡骨截肢者对肌电假肢的控制。该提案包括基于已证明有效的算法的模式识别控制包，为经桡骨截肢患者提供的创新手术技术，将大大提高他们控制假肢和接收感觉反馈的能力，以及先进的模式识别工具，将导致更强大的自适应控制。在这个项目中，我们将进行一系列的测试，这些测试将使用模式识别技术来改善对经桡骨假肢的控制。受试者将被允许将这些假体带回家进行为期一个月的试验，观察并纠正任何遗留的问题。有针对性的肌肉再神经支配（TMR）将在6名受试者中进行。TMR是一种新的外科技术，它将被切除的神经转移到多余的肌肉和皮肤上。它提供了新的肌电信号，可以直观地同时控制截肢者的功能，TMR将提高控制的准确性，可能被强大控制的类别的数量，并可能允许同时独立控制手和手腕。TMR允许对假肢进行更自然的控制，并提供有针对性的感觉反馈，在这种反馈中，受试者通过残肢上的再生神经皮肤感受他们被截肢的手。这两种手术方法将大大改善经桡骨假体的功能。TMR受试者也将进行实地试验。最后，研究了自适应模式识别技术和并行分类器技术。随着用户对分类器的适应，自适应控制可能对临床鲁棒性至关重要。平行控制将允许受试者同时控制手腕和手类，精度很高。这一提议将推动几个科学领域的发展，包括模式识别和神经再生生理学。平行分类器和自适应算法理论将大大发展超越目前的艺术状态，并且在缺乏已知类别的情况下，鲁棒性的概念将在肌电信号的背景下进行探索。这一建议也将促进我们对运动控制的理解，因为我们实施了这些新的控制技术，并为未来的实验提供支持，这将进一步发展我们对运动和感觉神经再生的理解。包括芝加哥康复研究所、新不伦瑞克大学和奥托博克公司在内的优秀团队已经组建起来。我们相信，拟议的研究将提高截肢者的护理标准。它也将成为继续改善假肢功能的重要研究平台。公共卫生相关性。这个项目将应用一种创新的手术技术来治疗经桡骨截肢患者，以改善他们对假肢的控制。它还将开发新技术，以推进具有更多功能的假肢的控制，包括手腕旋转，手腕屈伸和可以移动手指和拇指的手。这些研究将显著改善肘部以下截肢患者的假肢功能。