Regulatory clearance of a rehabilitation system for individuals with upper limb loss

上肢丧失患者康复系统的监管许可

• 批准号: 10710335
• 负责人: Rahul Reddy Kaliki
• 金额: $ 123.73万
• 依托单位: INFINITE BIOMEDICAL TECHNOLOGIES, LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-15 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710335
• 关键词: Amputation; Amputees; Businesses; Caring; Certification; Classification; Clinical; Clinical Research; Computer software; Contracts; Development; Devices; Documentation; Elbow; Electrodes; Electromagnetics; Elements; Hand; Individual; Learning; Limb structure; Lithium; Marketing; Measures; Methodology; Methods; Mission; Modeling; Motor; Muscle; Notification; Outcome; Outcome Measure; Patients; Pattern Recognition; Phase; Polymers; Process; Prosthesis; Radial; Rehabilitation therapy; Residual state; Safety; Signal Transduction; Surface; System; Technology; Testing; Time; Training; Transference; Upper Extremity; Validation; Work; Wrist; clinical care; design; efficacy evaluation; empowerment; experience; fabrication; flexibility; functional outcomes; functional restoration; improved; interest; limb loss; meetings; prospective; skills; verification and validation; virtual; visual feedback; wireless

ABSTRACT Our work to date has resulted in the development of several technologies focused on improving the lives of individuals with upper-limb loss (ULL). First, our Sense pattern recognition control system (and associated Element low-profile surface EMG electrodes and FlexCell flexible lithium-polymer batteries) can interface with most myoelectric hands, wrists, and elbows on the market. Second, our MyoTrain virtual-limb pre-prosthetic training system has been demonstrated to help individuals with ULL learn to use pattern recognition. This system is valuable in the “golden window” time period after amputation but before it is feasible to fit the patient with a definitive prosthesis. Based on our clinical experience, we identified three ways in which we could deepen our clinical impact, particularly as related to the MyoTrain system. First, we noted that EMG classification accuracy could be improved by decreasing intra-class scatter (improving repeatability) and/or increasing inter-class separation (improving separability). How individuals incorporate these methods is user specific and they could benefit from the incorporation of visual feedback – something that we call “Active Coaching”. Second, our business model allows us to provide MyoTrain to the patient before reimbursement is available, which offers significant clinical advantage. However, this currently still requires the prosthetist to fabricate a check socket for use with each individual. We now propose to integrate a reusable wireless armband which would eliminate this issue. Third, we plan to evaluate the efficacy of MyoTrain with a prospective trial of our technology suite and associated clinical methodology. Specifically, we will test three hypotheses: 1) use of MyoTrain results in skills transference to control of the final prosthesis; 2) the virtual outcome measures in MyoTrain are correlated with real-world functional outcome measures; and 3) use of MyoTrain results in improved clinical outcomes as measured by functional, subjective and usage metrics. The capstone of this project is the submission of a 510(k) premarket notification application for the MyoTrain system.

抽象的 迄今为止，我们的工作已经开发了多项技术，重点是改善人们的生活 首先，我们的 Sense 模式识别控制系统（以及相关的）。 元件薄型表面 EMG 电极和 FlexCell 柔性锂聚合物电池）可以与 市场上大多数肌电手、手腕和肘部，我们的 MyoTrain 虚拟肢体预假肢。 培训系统已被证明可以帮助 ULL 患者学习使用该系统。 在截肢后但在可以为患者安装假体之前的“黄金窗口”时间内很有价值 最终的假体。 根据我们的临床经验，我们确定了三种可以加深临床影响的方法， 特别是与 MyoTrain 系统相关的情况，首先，我们注意到 EMG 分类的准确性可能是 通过减少类内分散（提高重复性）和/或增加类间分离来改进 （提高可分离性）。个人如何结合这些方法是针对特定用户的，他们可以从中受益。 视觉反馈的结合——我们称之为“主动辅导”第二，我们的商业模式。 允许我们在报销可用之前向患者提供 MyoTrain，这提供了重要的临床意义 然而，目前这仍然需要假肢师制造一个检查插座以供使用。 我们现在建议集成一个可重复使用的无线臂带，以消除这个问题。 第三，我们计划通过对我们的技术套件进行前瞻性试验来评估 MyoTrain 的功效， 具体来说，我们将测试三个假设：1) 使用 MyoTrain 结果 技能转移到最终假肢的控制；2) MyoTrain 中的虚拟结果测量是 与现实世界的功能结果测量相关；3) 使用 MyoTrain 结果改善临床 通过功能、主观和使用指标来衡量的结果是该项目的顶峰。 提交 MyoTrain 系统的 510(k) 上市前通知申请。