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Grant: Discovery Grants Program - Individual

Université d'Ottawa

$27,000.00

Simulation-guided design of wearable assistive devices for improving human mobility

FY 2023-24

Summary
Wearable assistive devices can prevent injury, improve recovery, and enhance athletic performance. Several orthotic and prosthetic devices have been proposed, including exoskeletons comprising a rigid structure actuated by motors and "exosuits" comprising functional apparel equipped with tensioned cables. These devices may be portable (either unpowered or battery powered) or tethered to external equipment. Some devices are large, weight-bearing machines that transmit forces directly to the ground; others resemble form-fitting clothing. To date, wearable assistive devices have been developed primarily using experiments, but measurements alone provide little insight into the underlying mechanisms that determine a device's effectiveness. Understanding and predicting interactions between mechatronic devices and the body's neural, muscular, and skeletal systems is challenging: even ostensibly simple movements like walking are incredibly complex, involving precise coordination of dozens of muscles. Simulations help us understand human movement by providing biomechanical explanations for experimental observations, such as why ankle muscles are affected by an exoskeleton worn at the hip, and optimizations can accelerate development of assistive devices by enabling rapid exploration of proposed designs. Currently, the muscle-level effects of many devices are poorly understood: we lack the necessary analytical and predictive tools. This research will deepen our understanding of device-assisted movement through development, application, and dissemination of new methods and computational tools. We will develop methods for studying human-device interactions, such as the effect of gait adaptation on device performance, and will use these methods to simulate wearable assistive devices for patient populations. We will also develop new methods for obtaining high-quality estimates of skeletal kinematics from inertial measurement units, enabling analysis of device-assisted movement in natural environments. Our computational tools will be implemented and broadly disseminated in open-source software for immediate adoption by researchers, clinicians, roboticists, and others engaged in this rapidly developing field. The applications of this research are numerous and profound. Regular physical activity helps prevent hypertension, depression, and other serious illnesses. It is critical to advance our understanding of human movement and eliminate barriers to exercise for the millions of Canadian adults suffering from limited mobility. Wearable assistive devices have the potential to restore function to individuals with osteoarthritis, accelerate rehabilitation through continuous at-home monitoring, and protect us from injury. These devices are poised to replace walkers and wheelchairs, crutches and canes, improving the quality of life for individuals with limited mobility and extending the "healthspan" of older adults. Let's keep moving!
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2019-05726
Name nom
Uchida, Thomas
Department département
Mechanical Engineering
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2019
Award amount
27000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
2107
Research subject group en
Mechanical engineering
Research subject group fr
Modelling, simulation and finite element methods
Research subject en
Génie mécanique
Research subject fr
Modélisation, simulation et méthodes des éléments finis
Application title
Simulation-guided design of wearable assistive devices for improving human mobility
Keyword
assistive device; biomechanics; exoskeleton; human movement; modelling and simulation; musculoskeletal dynamics; neuromuscular control; optimization; parameter identification; simulation-guided design
Application summary
Wearable assistive devices can prevent injury, improve recovery, and enhance athletic performance. Several orthotic and prosthetic devices have been proposed, including exoskeletons comprising a rigid structure actuated by motors and "exosuits" comprising functional apparel equipped with tensioned cables. These devices may be portable (either unpowered or battery powered) or tethered to external equipment. Some devices are large, weight-bearing machines that transmit forces directly to the ground; others resemble form-fitting clothing. To date, wearable assistive devices have been developed primarily using experiments, but measurements alone provide little insight into the underlying mechanisms that determine a device's effectiveness. Understanding and predicting interactions between mechatronic devices and the body's neural, muscular, and skeletal systems is challenging: even ostensibly simple movements like walking are incredibly complex, involving precise coordination of dozens of muscles. Simulations help us understand human movement by providing biomechanical explanations for experimental observations, such as why ankle muscles are affected by an exoskeleton worn at the hip, and optimizations can accelerate development of assistive devices by enabling rapid exploration of proposed designs. Currently, the muscle-level effects of many devices are poorly understood: we lack the necessary analytical and predictive tools. This research will deepen our understanding of device-assisted movement through development, application, and dissemination of new methods and computational tools. We will develop methods for studying human-device interactions, such as the effect of gait adaptation on device performance, and will use these methods to simulate wearable assistive devices for patient populations. We will also develop new methods for obtaining high-quality estimates of skeletal kinematics from inertial measurement units, enabling analysis of device-assisted movement in natural environments. Our computational tools will be implemented and broadly disseminated in open-source software for immediate adoption by researchers, clinicians, roboticists, and others engaged in this rapidly developing field. The applications of this research are numerous and profound. Regular physical activity helps prevent hypertension, depression, and other serious illnesses. It is critical to advance our understanding of human movement and eliminate barriers to exercise for the millions of Canadian adults suffering from limited mobility. Wearable assistive devices have the potential to restore function to individuals with osteoarthritis, accelerate rehabilitation through continuous at-home monitoring, and protect us from injury. These devices are poised to replace walkers and wheelchairs, crutches and canes, improving the quality of life for individuals with limited mobility and extending the "healthspan" of older adults. Let's keep moving!