Application of Targeted Reinnervation for People with Transradial Amputation

描述(由申请人提供)：经桡骨截肢是最常见的大型上肢截肢手术，在过去十年中，估计占美国平民人口上肢截肢的40%，美国退伍军人人口的50%。大多数人由于创伤而经历了经桡骨截肢，他们都很年轻，需要假肢来恢复积极、富有成效的生活方式。目前的假体不能提供足够的功能，而新的多功能假体(能够许多不同的手握持)不能通过现有的控制策略进行充分的控制。功能不良是截肢者假体排斥发生率高的一个主要因素，这也是导致这些人残疾增加的原因之一。我们已经开发出一种名为靶向肌肉再神经(TMR)的外科技术，在这种技术中，曾经将重要控制信息传递到缺失肢体的切断神经被转移到新的“靶向”肌肉。在重新支配神经后，每当个体试图移动缺失的手臂时，目标肌肉就会收缩，产生可用于控制假肢中类似动作的电肌电信号。因此，TMR提供了对有价值但以前不可用的控制信息的访问。由CBM-RIC开发的模式识别算法可以解码这些丰富的EMG信息，以实现对更多功能的直观控制；用户只需尝试进行所需的手臂或手的运动。这项模式识别系统技术已经获得商业生产许可，并将在明年内投入临床应用。在高级手臂截肢者中，将TMR与模式识别相结合，大大改善了对更多自由度的控制，并且对用户来说控制更容易、更直观。这项多中心研究的目标是开发经桡骨TMR的手术技术，并通过临床试验比较TMR前后的模式识别控制和传统控制策略(TMR前)，评估TMR在经桡截肢者中的益处。正中神经和尺神经将被转移到前臂肌肉，这些神经携带着许多手握力所涉及的手内肌肉的控制信息。受试者将在为期8周的家庭试验中使用最先进的多功能假体-具有模式识别或传统控制-日常生活活动，随后进行全面的功能测试和用户调查。初步的身体和外科研究表明，经桡骨TMR是简单可行的；来自更高级别TMR截肢者的数据表明，当与模式识别相结合时，TMR可以改善对多手握持的控制。我们预计，具有模式识别功能的TMR将允许横断者更容易、更直观地控制更多的手抓握。开发跨桡骨的TMR将使这些人能够控制高度灵巧的假手。会的 这也无疑刺激了对先进控制系统的新研究，并使更先进的机电设备的开发成为可能。

DESCRIPTION (provided by applicant): Transradial amputation is the most common level of major upper limb amputation, accounting for an estimated 40% of upper limb loss in the US civilian population and 50% in the US military veteran population over the last decade. Most individuals experience transradial amputation due to trauma, are young, and need prostheses that allow them to resume an active, productive lifestyle. Current prostheses do not provide adequate function, and newer, multifunction prostheses (that are capable of many different hand grasps) cannot be adequately controlled by current control strategies. Poor function is a major factor in high rates of prosthesis rejection in transradial amputees, which contributes to increased disability for these individuals. We have developed a surgical technique, called targeted muscle reinnervation (TMR) in which severed nerves that used to carry important control information to the missing limb are transferred to new 'target' muscles. After reinnervation, the target muscles contract whenever the individual attempts to move their missing arm, generating electrical EMG signals that can be used to control analogous movements in a prosthesis. TMR thus provides access to valuable but previously unavailable control information. Pattern recognition algorithms, developed by CBM-RIC, can decode this rich EMG information to enable intuitive control of many more functions; the user simply has to attempt to make the desired arm or hand movement. This pattern recognition system technology has been licensed for commercial production and will be available for clinical implementation within the next year. Combining TMR with pattern recognition in higher-level arm amputees has resulted in substantially improved control of more DOFs, and control is easier and more intuitive for the user. The goal of this multicenter study is to develop surgical techniques for transradial TMR and to evaluate the benefits of TMR in transradial amputees by performing clinical trials to compare pattern recognition control, before and after TMR, with a conventional control strategy (before TMR). The median and ulnar nerves, which carry control information for intrinsic hand muscles involved in many hand grasps, will be transferred to forearm muscles. Subjects will use a state-of-the-art multifunction prosthesis-with either pattern recognition or conventional control-in activities of daily living during 8-week home trials, followd by comprehensive functional testing and user surveys. Preliminary cadaver and surgical studies indicate that transradial TMR is simple and feasible; data from higher-level TMR amputees indicate that when combined with pattern recognition, TMR provides improved control of multiple hand grasps. We expect that TMR, with pattern recognition, will allow transradial amputees to control more hand grasps more easily and more intuitively. Development of transradial TMR will enable these individuals to control highly dexterous prosthetic hands. It will also undoubtedly stimulate new research into advanced control systems and enable the development of more advanced mechatronic devices.