CAREER: Personalizing sensory-driven computerized interfaces to optimize motor rehabilitation

大脑或脊髓受伤的人经常接受体育训练，以恢复日常活动所需的运动能力。为了激励参与这种"运动疗法"，虚拟现实（VR）技术越来越多地被使用。VR可以被编程为高度逼真或看起来像游戏，以鼓励参与者。尽管如此，使用VR运动疗法的人并不总是比传统方法获得更好的结果，部分原因是它们不是针对每个用户的个性化。改善VR治疗需要更好地了解人们如何对可编程功能做出反应。可以改善VR运动疗法的两个特征是训练任务的难度和训练期间提供的指导（反馈）。刺激感官以获得更大沉浸感的VR界面可以很容易地使用增强感官反馈（ASF）提供训练指导。ASF的方法包括提供感官（例如，视觉、触觉）关于人在训练期间应当移动的方向和幅度的提示。该项目将研究功能障碍如何影响个人表现，生理反应和VR训练中的感知，以适应任务难度和ASF。该项目将通过对高中生的监督培训来促进教育，以定制开发VR康复应用程序。这些学生将通过向来自资源不足地区的K-12学生展示他们在实验室演示中的工作来进一步参与社区。此外，他们将从护理人员，临床医生以及最重要的是，作为最终用户导师的脊髓损伤（SCI）患者那里获得有关其应用程序的建设性反馈。 该项目将测试这样一个假设，即当适应VR训练功能时，运动表现会得到改善（即，任务的复杂性，ASF指导）的基础上的措施，表明健康和身体准备的培训。该项目的技术目标是：（1）创建回归型模型，将VR运动训练期间的表现与感知和生理测量相关联，并作为不同残疾的函数，以及（2）在自适应控制系统中利用这些模型，使用正强化来个性化VR训练功能。实验将包括SCI患者使用机器人手臂化身执行VR运动康复任务。该项目的重点是SCI人群，VR运动康复服务不足，但非常适合基础科学研究，因为SCI可以表现为有或没有认知障碍的身体残疾。参与者将生成在皮肤表面测量的肌肉激活信号，作为机器学习算法的输入，该算法检测控制化身的命令意图。来自VR环境、身体传感器和调查的数据将用于评估训练期间的表现、生理反应和感知变化。因此，该项目促进了以人为本的培训，在为临床医生提供患者特定数据的新的和不同的维度时考虑了身心，以个性化医疗保健，从而实现更好的功能。该项目有可能对用户设备界面如何最好地适应功能产生关键的见解，包括如何提供感官驱动的培训，以更直观地控制设备（例如，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Persons with an injury to the brain or spinal cord often undergo physical training to recover movement abilities needed for daily activities. To motivate participation in this “motor therapy,” virtual reality (VR) technologies are increasingly used. VR can be programmed to be highly realistic or look like a game to encourage participants. Still, persons who use VR motor therapy do not always achieve better outcomes than traditional methods, partially because they are not personalized to each user. Improving VR therapy requires a greater understanding of how persons respond to programmable features. Two features that can improve VR motor therapy are the difficulty of the training task and the guidance (feedback) provided during training. VR interfaces that stimulate senses for greater immersion can readily provide training guidance using augmented sensory feedback (ASF). The method of ASF involves providing sensory (e.g., visual, haptic) cues about the direction and magnitude in which a person should move during training. This project will examine how impairment in function affects personal performance, physiologic responses, and perceptions during VR training that adapts the task difficulty and ASF. This project will advance education through supervised training of high-school students to custom-develop VR rehabilitation applications. These students will further engage the community by presenting their work at laboratory demonstrations to K-12 students from under-resourced districts. In addition, they will receive constructive feedback about their applications from caregivers, clinicians, and, most importantly, persons with a spinal cord injury (SCI) serving as end-user mentors. The project will test the hypothesis that motor performance improves when adapting VR training features (i.e., task complexity, ASF for guidance) based on measures indicating well-being and physical readiness for training. This project’s technical objectives are: (1) creating regression-type models relating performance to perceptional and physiologic measures during VR motor training and as a function of varying disability, and (2) leveraging these models in an adaptive control system using positive reinforcement to personalize VR training features. Experiments will include persons with SCI performing VR motor rehabilitation tasks with a robot-arm avatar. This project focuses on the SCI population, under-served by VR motor rehabilitation yet ideal for fundamental scientific study since SCI can present as a physical disability with or without cognitive impairment. Participants will generate muscle-activation signals, measured at the skin surface, serving as inputs to a machine-learning algorithm that detects command intention in controlling the avatar. Data from the VR environment, body-mounted sensors, and surveys will be used to assess changes in performance, physiologic responses, and perceptions during training. As such, this project promotes human-centered training that considers both body and mind in providing clinicians with new and diverse dimensions of patient-specific data to personalize healthcare for better function. This project has the potential to generate critical insights into how user-device interfaces are best adapted for function, including how to deliver sensory-driven training for more intuitive control of devices (e.g., smartphones, vehicles, remote-controlled robots).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.