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

一名工程师创造了一种新的外骨骼设计，一名外科医生设想了一种新的髋关节置换手术程序。 但是他们如何在不对人类造成潜在伤害的情况下测试他们的发明呢？ 如何在不进行昂贵且耗时的原型设计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，这是美国食品和药物管理局最近批准的一项战略。 申请人正在开发先进的模型和计算机模拟，以预测人机或“生物机电”系统的运动。 使用这些模型，申请人已经创建了一种用于中风康复的新机器人，由人工智能（AI）引导的外骨骼的最佳控制器，优化髋关节植入物定位的术前规划方法，以及加拿大奥运会和残奥会运动员的最佳策略和设备。 为了创建可以信赖的计算机模拟来再现真实世界的现象，实验数据是必不可少的;本申请中要求的工具将提供我们研究所需的关键数据。 具体而言，所要求的摄像头和雷达系统将用于跟踪人类及其设备的运动，从而可以开发和验证我们的计算机模型。 所要求的系统将跟踪各种速度和位置的运动，应用范围包括轮椅篮球和冰壶，外骨骼辅助人类步态，高尔夫球，机器人辅助康复和骑自行车。 优化人类及其设备的性能需要非侵入式的运动测量，只能从所需的摄像机和雷达系统中获得，以验证我们在现实世界中的结果。 我们正在为机器人和外骨骼控制开发的AI算法，以及在没有人类和设备上繁琐标记的情况下跟踪运动的算法，需要所需工具可以提供的大量数据。 这项研究的意义是深远的。 中风是加拿大最常见的神经系统疾病，加拿大有426，000名幸存者，每年有50，000例新发病例。所要求的设备将支持个性化辅助和康复机器人的研究，由我们的人工智能算法提供动力，以优化运动康复。 加拿大每年有50，000例髋关节置换手术;植入物的错误定位导致4，250例矫正手术，这些手术可以通过术前预测模拟来避免。 优化的体育设备将支持我们的奥运会和残奥会运动员，以及在加拿大成立和初创的体育公司。仅高尔夫就为加拿大经济带来了200亿美元的收入。 生物机电一体化技术正在推动增长最快的行业之一; 2016年纳斯达克100指数前10名中有6家是生物技术公司。 加拿大在这一行业中具有竞争力至关重要，这需要投资于这里提出的研究。

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.