CAREER: Task-Level Coordination of Motor and Machine for Fluent Lower-Limb Prostheses

职业：流畅下肢假肢的电机和机器的任务级协调

• 批准号: 1943703
• 负责人: Patrick Wensing
• 金额: $ 53.01万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1943703&HistoricalAwards=false
• 关键词: CAREER; Task; Level; Coordination; Motor

This Faculty Early Career Development (CAREER) grant will enhance the comfort and safety of lower-limb prostheses by studying the interplay between human motor control loops and device control designs. Current powered lower-extremity prostheses offer benefits over previous passive devices in terms of providing work when ascending stairs and contributing actively to balance. The interface between a user and their powered device, however, results in complex physical dynamics and motor adaptations that both shape and are shaped by the control strategy of the prosthesis. This project will address this interplay by using models of the fundamental mechanics of human gait to coordinate machine response in synergy with task-level motor control goals, and to understand how machine response affects human gait. This project will promote the progress of science by providing understanding into how human motor coordination is affected by assistive device operation. It has potential to advance national health and wellbeing by reducing falls for above-knee amputees through the restoration of lower limb function. The project supports education and broadening participation through (1) after-school STEM programs serving at-risk middle school students; (2) enhancement of graduate and undergraduate curricula; and (3) a new graduate student summer school for Robotics at the Mind, Machine, and Motor Nexus.This CAREER project will study the dynamic interplay between users and their prostheses through low-dimensional template models of locomotion, which are hypothesized to reflect the intrinsic neural control of movement. Experiments will provide extensive data on natural human gait, non-amputee gait using a prosthesis with a bypass adapter, and amputee gait with passive and active prostheses. These data will be used to identify task-level human motor coordination goals and to understand how they are affected by injury and by device operation. Computable frameworks will be investigated to rigorously disambiguate between candidate template models in a quantitative and data-driven fashion using a hybrid optimal control approach. In parallel, a new paradigm for the task-level control of prostheses will be established, and experiments will assess its effects on measures of balance, gait symmetry, and user comfort. The use of an NSF-sponsored open-source prosthetic leg will accelerate the diffusion of the project's methods, thereby hastening achievement of translational impacts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该学院早期职业发展（CAREER）补助金将通过研究人类运动控制回路和设备控制设计之间的相互作用来提高下肢假肢的舒适性和安全性。当前的动力下肢假肢在上楼梯时提供工作并积极促进平衡方面提供优于先前的被动装置的益处。然而，用户和他们的动力装置之间的接口导致复杂的物理动力学和运动适应，其都塑造假体的控制策略并且由假体的控制策略塑造。该项目将通过使用人类步态的基本力学模型来协调机器响应与任务级运动控制目标的协同作用，并了解机器响应如何影响人类步态，从而解决这种相互作用。该项目将通过提供对辅助设备操作如何影响人类运动协调的理解来促进科学进步。它有可能通过恢复下肢功能减少膝上截肢者的福尔斯跌倒，从而促进国民健康和福祉。该项目通过以下方式支持教育和扩大参与：（1）为有风险的中学生提供课后STEM方案;（2）加强研究生和本科生课程;以及（3）一个新的研究生暑期学校，在头脑，机器和运动的关系机器人。这个职业项目将研究用户和他们的假肢之间的动态相互作用，通过低维模板模型的运动，这被假设为反映了运动的内在神经控制。实验将提供关于自然人类步态、使用带有旁路适配器的假肢的非截肢者步态以及使用被动和主动假肢的截肢者步态的大量数据。这些数据将用于识别任务级人体运动协调目标，并了解它们如何受到损伤和器械操作的影响。可计算的框架将进行调查，以严格消除候选模板模型之间的歧义，在定量和数据驱动的方式使用混合最优控制方法。与此同时，将建立假肢任务级控制的新范式，实验将评估其对平衡、步态对称性和用户舒适度指标的影响。使用NSF赞助的开源假肢将加速项目方法的传播，从而加速实现转化影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Finite-State Impedance and Direct Myoelectric Control for Robotic Ankle Prostheses: Comparing Their Performance and Exploring Their Combination

• DOI: 10.1109/tnsre.2023.3287971
• 发表时间: 2023-06
• 期刊: IEEE Transactions on Neural Systems and Rehabilitation Engineering
• 影响因子: 4.9
• 作者: Ryan R. Posh;J. Schmiedeler;Patrick M. Wensing

Optimizing Template Models to Quantifiably Assess Center of Mass Kinematic Reconstruction

优化模板模型以量化评估质量运动重建中心

• DOI: 10.1109/icorr55369.2022.9896496
• 发表时间: 2022
• 期刊: IEEE
• 作者: Kelly, David J.;Wensing, Patrick M.
• 通讯作者: Wensing, Patrick M.

Calibration of a tibia-based phase variable for control of robotic transtibial prostheses

用于控制机器人经胫骨假体的基于胫骨的相位变量的校准

• 发表时间: 2023
• 期刊: Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems
• 作者: Posh, Ryan R.;Tittle, Jonathan A.;Schmiedeler, James P.;Wensing, Patrick M.
• 通讯作者: Wensing, Patrick M.