Intelligent Assistive Technologies in Rehabilitation Engineering for People Living with Upper Limb Disabilities

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In Canada, 13.7% of adults are limited in their daily activities due to at least one disability. Many face challenges performing daily tasks and must rely on caregivers for assistance. This dependence is not viable in the long term. Indeed, a critical challenge Canada will be facing in the next 20 years is coping with its aging population, including an aging workforce. Indeed, demographic data indicates Canada's population over 65 years old is estimated to go from 16% in 2013 to 25% in 2026, and to 28% in 2061. More citizens will be affected by reduced independence and will be unable to fully participate socially and economically. Fewer resources will be available to care for those with disabilities and older adults, and there will be fewer workers in industry. This proposal outlines an innovative research program in rehabilitation engineering with the long-term objective of developing a new generation of innovative assistive technologies (ATs) based on rapidly advancing technologies 1) for people living with disabilities and older adults, to increase their autonomy and quality of life, and 2) for the prevention of injury for manual workers. In the context of this five-year research program, the short-term objectives are split into three themes where an interdisciplinary user-centered participative development methodology based on Design Thinking will be used, leveraging collaborative development and validation with engineering and rehabilitation researchers, healthcare professionals in clinical settings, and end users. Theme 1- Anticipatory control for movement disorder assistance: developing new concepts of anticipatory movement assistance that operate by detecting and reacting to involuntary movements before they happen. Theme 2- Intelligent multimodal control interfaces for assistive robot: developing a universal multi-sensor adaptable interface, harnessing sensor combination synergy through intelligent algorithms. Theme 3- Wearable individualized muscle overload feedback: developing individualized intelligent algorithms to integrate into biomedical wearable devices to estimate muscular overload and alert users in real time when they are in a state prone to injury. The proposed research program will lead to the training of 3 PhDs, 4 MScs and 5 BScs students in rehabilitation engineering, more specifically in the fields of robotics, mechatronics, artificial intelligence, advanced sensors, control interfaces, and medical devices. These fields are in great demand in the industry, and the trained HQP will become assets for Canadian companies or launch startups. We expect our research results to transfer directly to the industry, as they have in the past. ATs for older adults and people living with disabilities is a significant $23G market (2020) and is estimated to reach $32G by 2026. It is therefore critical for Canada to anticipate this trend by supporting research projects in this area, which will have both social and economic impacts.