Integrated System of Cameras and Radar for Markerless Measurement of Biomechatronic System Motions

一位工程师创造了一种新的外骨骼设计，一位外科医生设想了一种髋关节置换手术的新方法。但他们如何在不伤害人类的情况下测试他们的发明呢？如何在没有昂贵和耗时的原型和人体试验的情况下测试运动器材的新想法？答案在于预测动态计算机模拟，这一策略最近得到了美国食品和药物管理局（fda）的认可。

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.