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 (IMS) 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. The IMS research program 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 the mobility disabled population. The Ottawalk-speed hydraulic knee joint concept will be the basis for the next generation in knee joint control by providing appropriate variable dampening as a person with limited or negligible knee extensor capacity walks in their community (i.e., stairs, ramps, stumble recovery). Effective microprocessor-control of fluid flow should provide appropriate knee flexion resistance for safe movement but supply minimal resistance, when appropriate, for energy efficient gait. The only available variable resistance knee ankle foot orthosis (KAFO) is a prosthetic knee unit outfitted to a KAFO. The proposed Ottawalk device will innovate by providing a lighter, lower profile, and superior controlled device for improved mobility. In parallel with the Ottawalk orthosis research, research with the new Exolegs lower extremity robotic exoskeleton platform will be initiated. This new Canadian exoskeleton approach presents a viable platform for research on powered mobility for people with paralysis or bilateral lower extremity weakness. As a self-supporting walking frame, size and weight limitations are less severe. However, optimal mechanical function and control questions remain. To improve tools for biomechanical decision-making, wearable sensors, wearable video, and smartphone technologies will be combined to provide a better understanding of human movement outside the laboratory. Improving immediacy of biomechanical information should improve adoption of quantitative and evidence-based decision-making, potentially improving outcomes for people with movement deficits. Research is required on wearable and smartphone sensor acquisition and location, sensor fusion to generate usable outcomes, integrating outcomes with multimedia for augmented reality presentation, and determining effective real-time methods for integrating quantitative outcomes into clinical practice. This research will build on our recent smartphone application research to augment clinical tests, provided augmented reality analysis of body position, and improved activity classification from smartphone sensors and video. While prototype applications have been developed, pilot tests are needed to verify application performance in practice. Next-phase research will improve smartphone-based mobility activity classification for people with pathological gait (amputee, stroke, etc.), enhance video tools for real-time/augmented reality analysis of human movement, integrate new smartphone sensors into classification algorithms, and provide immediate smartphone-based analysis of human movement that can be used at the point of patient contact.