Intelligent Mobility Systems

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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.