Intelligent Mobility Systems

随着我们的人口老龄化，保持 身体活动能力对独立、生活质量和衰老都很重要 地点。需要技术和方法的融合才能进一步提高 老年人和行动不便的人如何行动。智能移动性 系统研究汇集了传感器辅助的实时信息 决策、移动控制和移动生成，以提供安全和 在一个人所选择的环境中进行有效的运动。智能移动性 系统涉及两个相互关联的流：智能可穿戴辅助设备 设备和实时运动评估。这两个流都需要实时 来自可穿戴传感器的多信号采集、特征提取、 分类，并输出以指导辅助设备功能或提供 为临床决策提供即时信息。智能助手 设备流还需要机械工程创新才能实现 可穿戴、耐用、成本适中的解决方案，可应用于移动性 残疾人口。 我们将继续研究我们的世界级 微处理器控制的液压膝关节，提供智能 对于膝关节伸肌能力可以忽略不计的人，提供可变的减震。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 了解用户意图，从而为用户提供最佳功能 当前活动。基于我们使用加拿大Arke外骨骼的经验 (动力膝盖和髋关节)和下肢假肢，新的研究将会改进 这些外骨骼机器人如何与人互动和新的机械设计 控制方法也将被用来创造新的技术 动力髋关节截肢假体(市场上没有)和动力髋关节假体 髋关节矫形器。 改善与移动性相关的 决策，下一阶段的研究将改善基于智能手机的 可穿戴传感器临床测试增强(即提供新的决策 执行标准的移动性测试时的信息，这不会是 不带可穿戴传感器系统)；增强视频工具 对人体运动的实时/增强现实分析(改进的标记 跟踪、面部分析等)；以及 研究新的深度相机方法，以获得即时运动质量 在公共生活空间(走廊等)内报道。这些创新将 在临床和老年护理环境中进行试点测试，以验证应用程序 在实践中的表现。

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.