Understanding and Enhancing Proprioception via Model-Based Human-Robot Interactions

通过基于模型的人机交互理解和增强本体感觉

• 批准号: 1934650
• 负责人: Jennifer Semrau
• 金额: $ 74.82万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1934650&HistoricalAwards=false
• 关键词: Understanding; Enhancing; Proprioception; via; Model

Proprioception is the sense of body position and movement that comes from specialized sensors in the joints and muscles of the body. Proprioception is impaired on one side of the body in about half of stroke survivors. The research objective of this project is to develop personalized robotic interventions targeting upper extremity rehabilitation for people with proprioceptive impairments after neurological injury such as stroke. The project will conduct human subject experiments, develop novel computational models, and use machine learning methods to enhance the design of personalized, subject-adaptive robotic interventions that are optimized for each individual's specific profile of impairment. This project will promote the progress of science and advance national health by developing new robotic therapies that have the potential to improve quality of life for a large number of people with sensorimotor impairments after stroke. Additionally, the work may increase national prosperity by reducing the healthcare cost burden of stroke through optimization of neurorehabilitative techniques and their robotic delivery. Broader impacts of the project include efforts to expose a diverse group of high school students to biomechanics through activities associated with National Biomechanics Day and a workshop to be developed.This project will examine how humans combine visual and proprioceptive information to estimate upper limb position, and then use these data to guide the development and testing of robot-aided rehabilitation in stroke survivors. The project will conduct three sets of activities: 1) human subject experiments exploiting human-robotic interactions to characterize stroke-related deficits of multisensory integration during the assessment of limb posture and movement; 2) the development of novel extensions to Bayesian models of multi-sensory integration and evaluation of their ability to describe impaired multisensory cue combination post-stroke; and 3) the design and implementation of individualized, robot-assisted, subject-adaptive training algorithms to rehabilitate multisensory function in upper limb impairment after stroke. This project advances the M3X program vision because it exploits human-robot interactions not only to interrogate the sensorimotor state of individuals after stroke, but to also drive improvement in sensorimotor function using an individualized robotic training approach.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.

本体感觉是身体的位置和运动感，它来自身体关节和肌肉中的特殊传感器。大约一半的中风幸存者的身体一侧本体感觉受损。该项目的研究目标是开发针对中风等神经损伤后本体感觉障碍患者的上肢康复的个性化机器人干预。该项目将进行人体实验，开发新的计算模型，并使用机器学习方法来加强个性化、主题适应的机器人干预的设计，这些干预针对每个人的特定损害情况进行优化。该项目将通过开发新的机器人疗法来促进科学进步和促进国民健康，这种疗法有可能改善大量中风后感觉运动障碍患者的生活质量。此外，这项工作可能会通过优化神经康复技术及其机器人交付来降低中风的医疗成本负担，从而增加国家的繁荣。该项目的更广泛影响包括努力通过与国家生物力学日相关的活动和即将开发的研讨会让不同的高中生接触生物力学。该项目将研究人类如何结合视觉和本体感知信息来估计上肢位置，然后使用这些数据来指导中风幸存者机器人辅助康复的开发和测试。该项目将开展三套活动：1)人类受试者实验，利用人与机器人的互动来表征与中风相关的肢体姿势和运动评估中的多感觉整合缺陷；2)开发多感觉整合的贝叶斯模型的新扩展，并评估其描述中风后受损的多感觉线索组合的能力；以及3)设计和实施个性化的、机器人辅助的、主题适应的训练算法，以恢复中风后上肢损伤的多感觉功能。该项目推进了M3X计划愿景，因为它不仅利用人与机器人的互动来询问中风后个人的感觉运动状态，而且还使用个性化的机器人训练方法来推动感觉运动功能的改善。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。