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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=737413
• 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.

随着我们的人口老龄化，保持身体的流动性对于独立、生活质量和适当的老龄化非常重要。需要技术和方法的融合，以进一步提高老年人和行动不便的人的行动方式。智能移动系统研究将实时信息、传感器辅助决策、运动控制和运动生成结合在一起，在个人选择的环境中提供安全有效的运动。智能移动系统涉及两个相互关联的流：智能可穿戴辅助设备和实时运动评估。这两个流都需要从可穿戴传感器进行实时多信号采集、特征提取、分类和输出，以指导辅助设备功能或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，以实现可穿戴、耐用、成本合适的解决方案，这些解决方案可以应用于行动不便的人群。我们将继续研究我们世界级的微处理器控制的液压膝关节，为膝关节伸展能力可以忽略不计的人提供智能可变减震。这需要独特的可穿戴传感器信号功能和机器学习方法，以更好地理解用户的意图，从而为当前活动提供最佳功能。基于我们在加拿大Arke外骨骼(动力膝盖和髋关节)和下肢假体方面的经验，新的研究将改善这些外骨骼机器人与人互动的方式，新的机械设计和控制方法也将用于创造动力髋关节假体(市场上尚不存在)和动力髋关节矫形器的新技术。为了改进与移动相关的决策，下一阶段的研究将改进基于智能手机和可穿戴传感器的临床测试增强(即，在执行标准的移动测试时提供新的决策信息，如果没有可穿戴的传感器系统，这将是无法实现的)；增强对人体运动的实时/增强现实分析的视频工具(改进的标记跟踪、面部分析等)；以及研究新的深度相机方法，以便在普通生活空间(走廊等)内立即报告运动质量。这些创新将在临床和老年护理环境中进行试点测试，以验证实践中的应用性能。