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，我们迄今为止的工作已开发了几种致力于改善生活的技术 上限损失（ULL）的个体。首先，我们的感官模式识别控制系统（以及相关的 元素低调的表面EMG电子和柔性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。第二，我们的Myotrain虚拟LIMB前旋转 已证明培训系统可帮助患有ULL的个人学习使用模式识别。这个系统 在截肢后的“黄金窗户”时期很有价值 确定的假体。 根据我们的临床经验，我们确定了三种方法可以加深临床影响： 特别是与Myotrain系统有关。首先，我们注意到EMG分类精度可能是 通过减少阶级散射（提高可重复性）和/或增加课堂间分离来改善 （改善分离）。个人如何合并这些方法是用户特定的，他们可以从中受益 视觉反馈的使用 - 我们称之为“积极教练”。其次，我们的业务模式 允许我们在报销之前向患者提供Myotrain，这提供了重要的临床 优势。但是，这目前要求假肢构造一个支票套接字以供与 每个人。现在，我们建议整合可重复使用的无线臂章，以消除此问题。 第三，我们计划通过对我们的技术套件的前瞻性试验来评估Myotrain的效率， 相关的临床方法。具体来说，我们将检验三个假设：1）使用Myotrain导致 技能转移以控制最终假体； 2）Myotrain的虚拟结局指标是 与现实世界的功能结果指标相关； 3）使用Myotrain会改善临床 结果通过功能，主观和使用指标来衡量。这个项目的顶峰是 提交Myotrain系统的510（k）上市通知申请。