SCH: Wearable Multi-Modal Sensing and Stimulation Arrays for Muscle-Aware Exoskeleton Control

SCH：用于肌肉感知外骨骼控制的可穿戴多模态传感和刺激阵列

• 批准号: 2124017
• 负责人: Nitin Sharma
• 金额: $ 109.55万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2124017&HistoricalAwards=false
• 关键词: SCH; Wearable; Multi; Modal; Sensing

Functional electrical stimulation (FES) and powered exoskeletons are promising rehabilitation interventions to promote the independence and recovery of persons with neurological injury. These interventions aim to encourage active participation of a user’s weak muscles to bring about substantial gains in recovery. A wearable sensor that measures the paralyzed muscle’s force can potentially inform the user’s participation levels, allowing personalization of FES or exoskeleton assistance. Current muscle sensors such as electromyography create poor representations of muscle force, mainly due to noise interference and incompatibility with FES. Instead, recent evidence suggests that ultrasound (US) enables high fidelity measurements of muscle strength due to its ability to visualize muscle activity directly. However, conventional US probes are hardly wearable, and their clinical deployment in FES systems and exoskeletons is nearly impossible. We plan a US-based sensing array technology to help devise new rehabilitation strategies that lead to faster recovery and smart health monitoring of muscles post a neurological injury such as spinal cord injury, stroke, multiple sclerosis, etc. The technology would be widely applicable in several medical problems that involve a human in the loop, including upper and lower extremity prostheses and exoskeletons, rehabilitation, and surgical robots. The research integrates outreach programs targeting K-12 students, talks and demos at a planetarium, and an annual summer program.The overall project objective is to create a new muscle-machine interface technology that combines dynamic in vivo ultrasound (US) imaging with electromyographic (EMG) signals for monitoring voluntary and FES-induced muscle activity. The individual objectives of the project are to 1) develop of a sensing array composed of EMG electrodes and ultrasound transducers, 2) use the feedback from the sensing arrays to synchronize exoskeleton assistance with a user’s impaired motor intent, and 3) validate the sensing array to measure muscle force changes due to FES, and 4) use the feedback from the sensing array to coordinate FES with an exoskeleton. Once successfully translated to practice, an ultrasound-based sensing array would help visualize muscle fibers’ contractile behavior and muscle force production, potentially in more than one imaging plane. Potentially, the array would facilitate symbiotic adjustment of the exoskeleton and FES assistance when integrated with the modeling and control framework.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.

功能性电刺激（FES）和动力外骨骼是有前途的康复干预措施，以促进神经损伤患者的独立性和恢复。这些干预措施旨在鼓励使用者的弱肌积极参与，以在恢复中带来实质性的收益。测量瘫痪肌肉力量的可穿戴传感器可以潜在地告知用户的参与水平，从而允许FES或外骨骼辅助的个性化。目前的肌肉传感器，如肌电图产生不良的肌肉力量的代表，主要是由于噪声干扰和不兼容的FES。相反，最近的证据表明，超声波（US）能够直接可视化肌肉活动，因此能够高保真测量肌肉力量。然而，传统的US探头几乎不可穿戴，并且它们在FES系统和外骨骼中的临床部署几乎是不可能的。我们计划在美国开发一种传感阵列技术，以帮助设计新的康复策略，从而在脊髓损伤、中风、多发性硬化症等神经损伤后实现更快的恢复和肌肉的智能健康监测。该技术将广泛应用于涉及人类的几个医疗问题，包括上下肢假肢和外骨骼、康复和手术机器人。该研究整合了针对K-12学生的外展计划，在天文馆的讲座和演示，以及每年的夏季计划。总体项目目标是创建一种新的肌肉-机器接口技术，该技术将动态体内超声（US）成像与肌电图（EMG）信号相结合，用于监测自愿和FES诱导的肌肉活动。该项目的各个目标是：1）开发由EMG电极和超声换能器组成的传感阵列，2）使用来自传感阵列的反馈将外骨骼辅助与用户受损的运动意图同步，以及3）验证传感阵列以测量由于FES引起的肌肉力量变化，以及4）使用来自传感阵列的反馈来协调FES与外骨骼。一旦成功地转化为实践，基于超声的传感阵列将有助于可视化肌肉纤维的收缩行为和肌肉力量的产生，可能在一个以上的成像平面。潜在地，当与建模和控制框架集成时，该阵列将促进外骨骼和FES援助的共生调整。该奖项反映了NSF的法定使命，并且通过使用基金会的智力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

Robust MPC-based Synergy Control of a Hybrid Neuroprosthesis for Foot Placement

用于足部放置的混合神经假体的基于 MPC 的鲁棒协同控制

• DOI: 10.1109/ccta49430.2022.9966170
• 发表时间: 2022
• 期刊: 2022 IEEE Conference on Control Technology and Applications (CCTA
• 作者: Lambeth, Krysten;Sun, Ziyue;Singh, Mayank;Sharma, Nitin
• 通讯作者: Sharma, Nitin

Quantitative Viscoelastic Response (QVisR) Domain Adaption with Fine Tuning

通过微调进行定量粘弹性响应 (QVisR) 域自适应

• DOI: 10.1109/ius54386.2022.9957979
• 发表时间: 2022
• 期刊: 2022 IEEE International Ultrasonics Symposium (IUS
• 作者: Richardson, Joseph B.;Gallippi, Caterina M.
• 通讯作者: Gallippi, Caterina M.