Neuromechanics-based Assistive Robotics

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Each year, millions of people lose their mobility due to aging and devastating neurological conditions. Neurological conditions, such as stroke and spinal cord injury (SCI), with more than half a million survivors and over 54 000 new cases per year in Canada, impair the mobility of individuals, lead to fall, decrease their quality of life and entail long-term health, economic and social consequence. Stroke and SCI each annually costs the Canadian economy $3.6 billion, while fall-related injuries impose an annual cost of $2 billion. ***While the assistive robotics systems and rehabilitation programs have shown potential to improve mobility, there are major challenges limiting their applicability and efficacy: 1) limitations of the current modelling of neuromechanics and sensorimotor deficits in accounting for natural dynamics and loading and bi-articular muscles effect, 2) absence of a reliable motor function monitoring system during activity of daily life (ADL), 3) limited understanding of human-robot interaction in robotic systems and the subject-specific characteristics of interaction resulting in suboptimal assistive control. In response to these challenges, this research will contribute to building a comprehensive neuromechanical model of locomotion and developing of personalized assistive robotics systems. There are 3 main objectives within the proposed 5-year research program.***By developing advanced system identification and machine learning techniques to analyze the perturbation data collected from exoskeletons, we will build novel models of neuromechanics and multi-joint impedance. Simple techniques will be developed for quantitative modelling of spasticity. ***We will provide an accurate evaluation of motor alternation and gait stability during ADL by developing novel smart shoes integrating several sensory modalities. The outcomes of this research will be used to find the influential neuromechanics aspects on motor function.***We will investigate human-robot co-adaptation and learning using exoskeleton experiments, data-driven models and novel movement intention decoders. ***The proposed research will form a knowledge foundation of human neuromechanics and motor deficits enabling the new generation of personalized assistive robotics systems to be tailored to the needs of each affected individual. It will greatly contribute to the improvement of their independence and quality of life, and can thus be of major social health and economic value. The spasticity modelling techniques and the smart shoes have commercialization potential.***Students will develop professional engineering skills in biomechanics and health engineering, robotics and control and data science through this multidisciplinary research program. My students will be able to boost the development of novel rehabilitation technologies that will benefit the Canadian economy and healthcare system.