Intelligent Mobility Systems

智能移动系统

• 批准号: RGPIN-2019-04106
• 负责人: Lemaire, Edward
• 金额: $ 2.33万
• 依托单位: University of Ottawa
• 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=714635
• 关键词: Intelligent; Mobility; Systems

As our population ages, maintaining physical mobility is important for independence, quality of life, and aging in place. A convergence of technologies and methods are needed to further enhance how the elderly and people with mobility deficits move. Intelligent Mobility Systems research brings together real-time information, sensor-aided decision-making, movement control, and movement generation to provide safe and effective locomotion in a person's chosen environment. Intelligent Mobility Systems involves two inter-related streams: intelligent-wearable assistive devices and real-time movement evaluation. Both streams require real-time multi-signal acquisition from wearable sensors, feature extraction, classification, and output to either guide assistive device function or provide immediate information for clinical decision-making. The intelligent assistive device stream also requires mechanical engineering innovations to achieve wearable, durable, cost appropriate solutions that can be applied across mobility disabled populations. Research will continue on our world-class microprocessor controlled hydraulic knee joint that provides intelligent variable dampening for person with negligible knee extensor capacity. This requires unique wearable sensor signal features and machine learning methods to better understand the user's intent, thereby providing optimal function for the current activity. Building on our experience with the Canadian ARKE exoskeleton (powered knees and hips) and lower limb prosthetics, new research will improve how these exoskeleton robots interact with the person and new mechanical-design and control approaches will also be used to create novel technologies for powered hip-amputation prostheses (does not exist on the market) and powered hip orthoses. To improve mobility-related decision-making, next-phase research will improve smartphone-based and wearable-sensor clinical test augmentation (i.e., provide new decision-making information when performing standard mobility tests, which would not be available without the wearable sensor system); enhance video tools for real-time/augmented reality analysis of human movement (improved marker tracking, facial analysis, etc.); and investigate new depth camera approaches for immediate movement quality reporting within common living spaces (hallways, etc.). These innovations will be pilot tested in clinical and eldercare environments to verify application performance in practice.

随着人口老龄化， 身体活动能力对独立性、生活质量和衰老都很重要， 地方需要融合各种技术和方法， 老年人和行动不便的人是如何移动的。智能移动 系统研究汇集了实时信息，传感器辅助 决策、运动控制和运动生成， 在一个人所选择的环境中有效的运动。智能移动 系统涉及两个相互关联的流：智能穿戴辅助 设备和实时运动评估。两个流都需要实时 可穿戴传感器的多信号采集，特征提取， 分类，并输出以引导辅助设备功能或提供 为临床决策提供即时信息。智能辅助 设备流还需要机械工程创新来实现 可穿戴、耐用、成本合理的解决方案，可应用于各种移动性 残疾人群体。 研究将继续在我们的世界级 微处理器控制的液压膝关节， 可变阻尼的人可以忽略膝盖伸肌的能力。这需要 独特的可穿戴传感器信号特征和机器学习方法， 理解用户的意图，从而为用户提供最佳功能。 当前活动。基于我们对加拿大ARKE外骨骼的经验， （动力膝盖和臀部）和下肢假肢，新的研究将改善 这些外骨骼机器人如何与人互动， 和控制方法也将用于创造新的技术， 电动髋关节截肢假体（市场上不存在）和电动 髋矫形器 改善与流动性有关的 决策，下一阶段的研究将改善基于智能手机和 可穿戴传感器临床测试增强（即，提供新的决策 在执行标准移动性测试时， 不带可穿戴传感器系统）;增强视频工具， 人的运动的实时/增强现实分析（改进的标记 跟踪、面部分析等）; 和 研究用于即时运动质量的新深度相机方法 在公共生活空间（走廊等）内报告。这些创新将 在临床和老年护理环境中进行试点测试，以验证应用 在实践中的表现。