Neuromechanics-based Assistive Robotics

基于神经力学的辅助机器人

• 批准号: RGPIN-2018-04850
• 负责人: Arami, Arash
• 金额: $ 1.97万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712428
• 关键词: Neuromechanics; based; Assistive; Robotics

Each year, millions of people lose their mobility due to aging and devastating neurological conditions. Neurological conditions, such as stroke and spinal cord injury (SCI), with more than half a million survivors and over 54 000 new cases per year in Canada, impair the mobility of individuals, lead to fall, decrease their quality of life and entail long-term health, economic and social consequence. Stroke and SCI each annually costs the Canadian economy $3.6 billion, while fall-related injuries impose an annual cost of $2 billion. While the assistive robotics systems and rehabilitation programs have shown potential to improve mobility, there are major challenges limiting their applicability and efficacy: 1) limitations of the current modelling of neuromechanics and sensorimotor deficits in accounting for natural dynamics and loading and bi-articular muscles effect, 2) absence of a reliable motor function monitoring system during activity of daily life (ADL), 3) limited understanding of human-robot interaction in robotic systems and the subject-specific characteristics of interaction resulting in suboptimal assistive control. In response to these challenges, this research will contribute to building a comprehensive neuromechanical model of locomotion and developing of personalized assistive robotics systems. There are 3 main objectives within the proposed 5-year research program. By developing advanced system identification and machine learning techniques to analyze the perturbation data collected from exoskeletons, we will build novel models of neuromechanics and multi-joint impedance. Simple techniques will be developed for quantitative modelling of spasticity. We will provide an accurate evaluation of motor alternation and gait stability during ADL by developing novel smart shoes integrating several sensory modalities. The outcomes of this research will be used to find the influential neuromechanics aspects on motor function. We will investigate human-robot co-adaptation and learning using exoskeleton experiments, data-driven models and novel movement intention decoders. The proposed research will form a knowledge foundation of human neuromechanics and motor deficits enabling the new generation of personalized assistive robotics systems to be tailored to the needs of each affected individual. It will greatly contribute to the improvement of their independence and quality of life, and can thus be of major social health and economic value. The spasticity modelling techniques and the smart shoes have commercialization potential. Students will develop professional engineering skills in biomechanics and health engineering, robotics and control and data science through this multidisciplinary research program. My students will be able to boost the development of novel rehabilitation technologies that will benefit the Canadian economy and healthcare system.

每年，数百万人因衰老和破坏性的神经系统疾病而失去行动能力。神经系统疾病，如中风和脊髓损伤（SCI），在加拿大每年有50多万幸存者和54000多例新病例，损害了个人的活动能力，导致跌倒，降低了他们的生活质量，并带来长期的健康，经济和社会后果。中风和SCI每年给加拿大经济造成36亿美元的损失，而与跌倒有关的伤害每年造成20亿美元的损失。 虽然辅助机器人系统和康复计划已显示出改善移动性的潜力，但仍存在限制其适用性和有效性的主要挑战：1）神经力学和感觉运动缺陷的当前建模在解释自然动力学和负荷以及双关节肌肉效应方面的局限性，2）在日常生活活动（ADL）期间缺乏可靠的运动功能监测系统，3）对机器人系统中人机交互的理解有限，以及交互的对象特定特征导致次优辅助控制。针对这些挑战，本研究将有助于建立一个全面的运动神经力学模型和个性化的辅助机器人系统的发展。在五年研究计划中有三个主要目标。 通过开发先进的系统识别和机器学习技术来分析从外骨骼收集的扰动数据，我们将建立新的神经力学和多关节阻抗模型。简单的技术将被开发用于痉挛的定量建模。 我们将通过开发集成多种感觉方式的新型智能鞋，提供ADL期间运动交替和步态稳定性的准确评估。本研究的结果将被用来寻找影响运动功能的神经力学方面。 我们将使用外骨骼实验，数据驱动模型和新颖的运动意图解码器来研究人机协同适应和学习。 拟议的研究将形成人类神经力学和运动缺陷的知识基础，使新一代个性化辅助机器人系统能够根据每个受影响个体的需求量身定制。这将大大有助于提高他们的独立性和生活质量，因此具有重大的社会健康和经济价值。痉挛建模技术和智能鞋具有商业化潜力。 学生将通过这个多学科研究项目培养生物力学和健康工程、机器人技术以及控制和数据科学方面的专业工程技能。我的学生将能够促进新的康复技术的发展，这将有利于加拿大的经济和医疗保健系统。