Grant: Research Tools and Instruments
University of Waterloo
$87,573.00
Integrated System of Cameras and Radar for Markerless Measurement of Biomechatronic System Motions
FY 2020-21
Summary
An engineer has created a new exoskeleton design, and a surgeon envisions a new procedure for hip replacement surgery. But how do they test their inventions without potential harm to a human? How does one test new ideas for sports equipment, without expensive and time-consuming prototyping and human trials? The answer lies in predictive dynamic computer simulations, a strategy recently endorsed by the US Food and Drug Administration.
The applicant is developing advanced models and computer simulations to predict the movement of human-machine, or “biomechatronic”, systems. Using these models, the applicant has created a new robot for stroke rehabilitation, optimal controllers for exoskeletons guided by artificial intelligence (AI), pre-surgical planning methods to optimize hip implant positioning, and optimal strategies and equipment for Canada's Olympians and Paralympians.
To create computer simulations that can be trusted to reproduce real-world phenomena, experimental data is essential; the tools requested in this application will provide the critical data that is needed for our research. Specifically, the requested cameras and radar system will be used to track the movements of a human and their equipment, from which our computer models can be developed and validated. The requested system will track motions over a wide range of speeds and positions, with applications ranging from wheelchair basketball and curling, exoskeleton-assisted human gait, golfing, robot-assisted rehabilitation, and cycling.
Optimizing the performance of humans and their equipment requires non-intrusive measurements of movement, obtainable only from the requested cameras and radar system, to validate our results in real-world settings. The AI algorithms we are developing for robot and exoskeleton control, and for the tracking of movements without cumbersome markers on humans and equipment, demand large volumes of data that the requested tools can provide.
The implications of this research are profound. Stroke is the most prevalent neurological condition in Canada, with 426,000 survivors in Canada and 50,000 new cases per year. The equipment requested will support research into personalized assistive and rehabilitation robots, powered by our AI algorithms, to optimize motor recuperation. There are 50,000 hip replacement surgeries in Canada each year; faulty positioning in implants results in 4,250 corrective surgeries that could be avoided using pre-surgical predictive simulations. Optimized sports equipment will support our Olympic and Paralympic athletes, as well as established and start-up sports companies in Canada. Golf alone generates $20 billion for the Canadian economy. Biomechatronics technology is fueling one of the fastest growing industries; 6 of the top-10 performers in the NASDAQ-100 index in 2016 were biotech companies. It is vital for Canada to be competitive in this industry, which requires investment in research such as that proposed here.
Program
Research Tools and Instruments
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RTI-2021-00133
Name nom
McPhee, John
Department département
Systems Design Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2021
Award amount
87573
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1612
Committee name en
Mechanical Engineering (RTI)
Committee name fr
Génie mecanique (OIR)
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2107
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Modelling, simulation and finite element methods
Research subject fr
Modélisation, simulation et méthodes des éléments finis
Installment
inst:1-1
Partie
1
Nb partie
1
Application title
Integrated System of Cameras and Radar for Markerless Measurement of Biomechatronic System Motions
Keyword
NSERC
Application summary
An engineer has created a new exoskeleton design, and a surgeon envisions a new procedure for hip replacement surgery. But how do they test their inventions without potential harm to a human? How does one test new ideas for sports equipment, without expensive and time-consuming prototyping and human trials? The answer lies in predictive dynamic computer simulations, a strategy recently endorsed by the US Food and Drug Administration.
The applicant is developing advanced models and computer simulations to predict the movement of human-machine, or “biomechatronic”, systems. Using these models, the applicant has created a new robot for stroke rehabilitation, optimal controllers for exoskeletons guided by artificial intelligence (AI), pre-surgical planning methods to optimize hip implant positioning, and optimal strategies and equipment for Canada's Olympians and Paralympians.
To create computer simulations that can be trusted to reproduce real-world phenomena, experimental data is essential; the tools requested in this application will provide the critical data that is needed for our research. Specifically, the requested cameras and radar system will be used to track the movements of a human and their equipment, from which our computer models can be developed and validated. The requested system will track motions over a wide range of speeds and positions, with applications ranging from wheelchair basketball and curling, exoskeleton-assisted human gait, golfing, robot-assisted rehabilitation, and cycling.
Optimizing the performance of humans and their equipment requires non-intrusive measurements of movement, obtainable only from the requested cameras and radar system, to validate our results in real-world settings. The AI algorithms we are developing for robot and exoskeleton control, and for the tracking of movements without cumbersome markers on humans and equipment, demand large volumes of data that the requested tools can provide.
The implications of this research are profound. Stroke is the most prevalent neurological condition in Canada, with 426,000 survivors in Canada and 50,000 new cases per year. The equipment requested will support research into personalized assistive and rehabilitation robots, powered by our AI algorithms, to optimize motor recuperation. There are 50,000 hip replacement surgeries in Canada each year; faulty positioning in implants results in 4,250 corrective surgeries that could be avoided using pre-surgical predictive simulations. Optimized sports equipment will support our Olympic and Paralympic athletes, as well as established and start-up sports companies in Canada. Golf alone generates $20 billion for the Canadian economy. Biomechatronics technology is fueling one of the fastest growing industries; 6 of the top-10 performers in the NASDAQ-100 index in 2016 were biotech companies. It is vital for Canada to be competitive in this industry, which requires investment in research such as that proposed here.