Simultaneous Pattern Recognition Control of Powered Upper Limb Prostheses

动力上肢假肢的同步模式识别控制

• 批准号: 9345731
• 负责人: Blair Lock
• 金额: $ 46.92万
• 依托单位: COAPT, LLC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-12-07 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9345731
• 关键词: Adopted; Agonist; Algorithms; Amputees; Artificial Arm; Clinical; Computer software; Cross-Over Studies; Data; Development; Devices; FDA approved; Freedom; Future; Generations; Goals; Home environment; Individual; Institutional Review Boards; Intuition; Limb Prosthesis; Limb structure; Literature; Manufacturer Name; Movement; Muscle; Myoelectric prosthesis; Notification; Outcome; Participant; Pattern Recognition; Pattern Recognition Systems; Performance; Persons; Phase; Population; Posture; Procedures; Process; Prosthesis; Public Health; Quality of life; Questionnaires; Randomized; Research; Signal Transduction; Site; Small Business Innovation Research Grant; System; Technology; Testing; Time; Update; Upper Extremity; Voice; Work; arm; clinical application; disability; expectation; experimental study; improved; limb amputation; myoelectric control; new technology; next generation; patient population; powered prosthesis; prosthesis control; psychologic; reinnervation; research and development; social; standard of care; trend; usability; virtual; virtual reality; week trial

Project Summary/Abstract Upper limb amputation is a significant cause of disability that drastically limits an individual's functional capabilities and can also have profound psychological and social effects. Although prosthetic devices are currently the best treatment option for upper limb amputation, even the most technologically advanced prosthetic arms fail to adequately restore the functional capabilities of the lost arm. Myoelectric prosthesis control using pattern recognition was first introduced to the commercial market by Coapt, LLC in late 2013. It provides more natural and intuitive control and eliminates the need for mode switching and the requirement for strong and isolated EMG signals from agonist/antagonist muscle sites. However, the current system is limited to providing control of only one prosthesis movement at a time. The need for simultaneous control of multiple movements has been long cited in the literature and is often voiced by clinicians in the field. The proposed project is to finalize and implement a simultaneous control algorithm in Coapt, LLC's next-generation commercial pattern recognition controller. The long-term goal of this application is to advance the field of upper-limb prosthetics by providing a state-of-the-art control system with unprecedented functionality and ease of use. The specific aims of the proposal are to (1) implement the recently developed simultaneous control algorithm on Coapt's next-generation commercial controller and (2) evaluate the simultaneous control algorithm in a home trial. Under the first aim, the simultaneous control algorithm will be incorporated into the next-generation system's firmware and user interface software and then optimized to minimize processing time. If necessary, hardware updates will be made to accommodate the increased processing load, and the resulting system will be fully tested and validated. Under the second aim, an IRB-approved randomized crossover study will be performed. Participants will use the system with and without simultaneous control capabilities at home for two 8-week trial periods and will perform virtual control tasks and complete a questionnaire at the end of each trial period. The system will also collect usage data during each trial. All data will be analyzed to determine wear-time under each control strategy, preferred control strategy, and frequently selected simultaneous movements. This proposed work is fully expected to result in a commercial product, including the FDA premarket notification process, within a short time of project completion.

项目概要/摘要 上肢截肢是导致残疾的一个重要原因，它极大地限制了个人的功能能力，并且可以 还具有深远的心理和社会影响。尽管假肢装置是目前最好的治疗选择 上肢截肢后，即使是技术最先进的假肢也无法充分恢复功能 失去手臂的能力。 使用模式识别的肌电假肢控制最晚由 Coapt, LLC 引入商业市场 2013.它提供了更自然和直观的控制，消除了模式切换的需要和对 来自激动剂/拮抗剂肌肉部位的强烈且孤立的肌电图信号。然而，当前的系统仅限于提供 一次仅控制一个假肢运动。同时控制多个动作的需求由来已久 在文献中被引用，并且经常被该领域的临床医生表达。 拟议的项目是在 Coapt, LLC 的下一代系统中最终确定并实施同步控制算法 商业模式识别控制器。该应用程序的长期目标是推进上肢领域的发展 通过提供具有前所未有的功能和易用性的最先进的控制系统来实现假肢。具体目标 该提案的主要内容是 (1) 在 Coapt 的下一代上实施最近开发的同步控制算法 商业控制器和（2）在家庭试验中评估同步控制算法。在第一个目标下， 同步控制算法将被纳入下一代系统的固件和用户界面软件中 然后进行优化以最小化处理时间。如有必要，将进行硬件更新以适应增加的 处理负载，所得系统将经过全面测试和验证。根据第二个目标，IRB 批准 将进行随机交叉研究。参与者将在同步控制和非同步控制的情况下使用该系统 在家进行两个为期 8 周的试用期，并将执行虚拟控制任务并在最后完成调查问卷 每个试用期。该系统还将在每次试用期间收集使用数据。所有数据将被分析以确定磨损时间 在每个控制策略下，优选的控制策略以及经常选择的同时运动。这项拟议的工作 完全有望在短时间内推出商业产品，包括 FDA 上市前通知流程 项目完成。