Collaborative Research: User-Optimal Robotic Prosthesis Design

这个合作研究项目的目标是开发优化机器人踝足假肢功能的方法，以满足个人用户的需求。该方法是开发人-假体相互作用的计算模型，使用它们来预测最佳设备设计，并在多功能机器人试验台的实验工作中改进预测。一个详细的肌肉骨骼截肢运动仿真模型，可调用户特定的属性，将被生成。数值优化将用于获得对特定用户最优的设计，并对用户特征的微小变化保持稳健。设计将在测量人类能量使用、肌肉活动、身体力学和平衡的实验中向人类受试者展示“通用踝足假肢模拟器”。实验结果将用于生成具有高预测精度的模型。这项研究将产生一种经过验证的软件工具，供临床医生为个体患者制定最佳假体设计。如果成功，这项研究的好处将是提高截肢者的活动能力和生活质量，通过一个软件工具来指导用户最佳机器人踝足假肢的设计。例如，该研究预计将量化更强大，但更重，更昂贵的电机的成本和效益之间的权衡，从而为个人用户提供最佳产品设计。由此产生的设备有望减少美国100多万下肢截肢者的步行速度、疲劳、福尔斯和疼痛等慢性问题。这种方法和基础设施也有望改善生物机电设计过程，例如改善康复机器人的设计。这项研究将为学生提供一个合作的，跨学科的环境，包括少数民族，女性和残疾人。

The objective of this collaborative research project is to develop methods for optimizing robotic ankle-foot prosthesis function to the needs of individual users. The approach is to develop computational models of human-prosthesis interaction, use them to predict optimal device designs, and refine predictions in experimental work with a versatile robotic testbed. A detailed musculoskeletal simulation model of amputee locomotion, with tunable user-specific properties, will be generated. Numerical optimization will be used to obtain designs that are optimal for specific users and robust to small changes in user characteristics. Designs will be presented to human subjects with a "universal ankle-foot prosthesis emulator" in experiments that measure human energy use, muscle activity, body mechanics, and balance. Experimental results will be used to generate a model with high predictive accuracy. The research will result in an empirically-validated software tool for use by clinicians in prescribing optimal prosthesis designs to individual patients. If successful, the benefit of this research will be improved mobility and quality of life for individuals with amputation, achieved through a software tool that guides the design of user-optimal robotic ankle-foot prostheses. For example, the research is expected to quantify trade-offs between the costs and benefits of more powerful, but heavier and more expensive, motors, allowing optimal product design for individual users. The resulting devices are expected to reduce chronic problems with walking speed, fatigue, falls, and pain for more than 1 million people with lower-limb amputation in the United States. This methodology and infrastructure is also expected to improve biomechatronic design processes in general, for example improving the design of rehabilitation robots. The research will provide a collaborative, interdisciplinary environment for students, including minority, female, and disabled individuals.