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体功能的方法，以满足个人用户的需求。该方法是开发人类假肢相互作用的计算模型，使用它们来预测最佳设备设计，并在多功能机器人测试平台的实验工作中改进预测。将生成一个详细的截肢者运动肌肉骨骼模拟模型，具有可调的用户特定属性。数值优化将用于获得对特定用户最优的设计，并且对用户特征的微小变化具有鲁棒性。设计将呈现给人类受试者与“通用踝足假体模拟器”在实验中测量人体能量使用，肌肉活动，身体力学，和平衡。实验结果将用于生成具有较高预测精度的模型。该研究将产生一个经验验证的软件工具，供临床医生使用，为个别患者开具最佳假体设计处方。如果成功，这项研究的好处将是通过一个软件工具来指导用户优化机器人踝足假体的设计，从而改善截肢患者的行动能力和生活质量。例如，这项研究有望量化更强大、但更重、更昂贵的电机的成本和收益之间的权衡，从而为个人用户提供最佳的产品设计。由此产生的设备有望为美国100多万下肢截肢者减少步行速度、疲劳、跌倒和疼痛等慢性问题。这种方法和基础设施也有望改善一般的生物机电设计过程，例如改善康复机器人的设计。这项研究将为学生，包括少数民族、女性和残疾人提供一个协作的、跨学科的环境。

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.