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.

摘要 迄今为止，我们的工作已经导致了几项专注于改善人类生活的技术的发展。 上肢缺失（Upper-limb loss，缩写为HLS）。首先，我们的Sense模式识别控制系统（以及相关的 Element低轮廓表面EMG电极和FlexCell柔性锂聚合物电池）可与 市场上大多数肌电手、手腕和肘部。其次，我们的MyoTrain虚拟假肢 训练系统已被证明可以帮助患有自闭症的个人学习使用模式识别。该系统 在截肢后的“黄金窗口”时间段内，但在为患者提供合适的治疗方案之前， 永久性假肢 根据我们的临床经验，我们确定了三种方法来加深我们的临床影响， 特别是与MyoTrain系统相关的。首先，我们注意到EMG分类准确性可能是 通过减少类内分散（提高可重复性）和/或增加类间分离来改善 （提高可分离性）。个人如何结合这些方法是用户特定的，他们可以受益于 视觉反馈的结合--我们称之为“主动指导”。第二，我们的商业模式 允许我们在报销之前向患者提供MyoTrain，这提供了重要的临床 优势然而，这目前仍然需要修复师制造一个检查插座， 每一个人我们现在建议集成一个可重复使用的无线臂带，这将消除这个问题。 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的疗效， 相关临床方法学。具体来说，我们将测试三个假设：1）使用MyoTrain导致 将技能转移到最终假体的控制; 2）MyoTrain中的虚拟结果指标是 与真实世界功能结局指标相关; 3）使用MyoTrain可改善临床 通过功能、主观和使用指标衡量的结果。这个项目的顶点是 提交MyoTrain系统的510（k）上市前通知申请。