CT imaging-based prediction and stratification of motor and cognitive behavior after stroke for targeted game-based robot therapy: Diversity Supplement

基于 CT 成像的中风后运动和认知行为的预测和分层，用于基于游戏的有针对性的机器人治疗：多样性补充

• 批准号: 10765218
• 负责人: MICHELLE J. JOHNSON
• 金额: $ 1.88万
• 依托单位: RECUPERO ROBOTICS LLC
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10765218
• 关键词: Adult; Adverse event; Algorithms; Behavior; Brain; Brain imaging; Caring; Characteristics; Clinic; Clinical; Cognition; Cognitive; Collaborations; Communities; Compensation; Control Groups; Data; Day Care; Developing Countries; Docking; Dose; Environment; Equation; Exercise; Feedback; Fingers; Freedom; Frequencies; Friends; Goals; Health; Health Care Costs; Health Insurance; Health care facility; Heart Rate; Hospitals; Hour; Image; Impaired cognition; Impairment; Individual; Infrastructure; Insurance Coverage; Intelligence; Intervention; Lead; Lesion; Lower Extremity; Monitor; Motivation; Motor; Movement; Muscle; Nursing Homes; Occupational Therapy; Parents; Patients; Performance; Persons; Phase; Physical therapy; Play; Play Therapy; Population; Positioning Attribute; Randomized; Rehabilitation Centers; Rehabilitation therapy; Residual state; Resource-limited setting; Resources; Robot; Robotics; Rural; Safety; Scanning; Speech Therapy; Stratification; Stroke; System; Talents; Technology; Testing; Therapeutic; Time; Torque; Training; Upper Extremity; X-Ray Computed Tomography; arm; base; care burden; cognitive function; cohort; community based care; cost; design; disability; doctoral student; exercise rehabilitation; experience; force feedback; functional improvement; functional outcomes; grasp; haptics; health care disparity; imaging modality; imaging platform; improved; innovative technologies; insight; motor control; motor impairment; motor recovery; multidisciplinary; neural; neurological rehabilitation; novel; nursing skill; parent grant; parent project; personalized care; personalized medicine; post stroke; pre-doctoral; prediction algorithm; recruit; rehabilitation technology; rehabilitative care; robot assistance; robot control; robot rehabilitation; robot therapy; safety testing; sensor; stroke patient; stroke survivor; stroke therapy; success; targeted treatment; treatment duration; treatment group; usability

Project Summary With stroke being the leading cause of disability worldwide, there is a need to improve current rehabilitative care. Furthermore, the burden of care is significant, and many developing countries do not have the resources necessary to treat people with stroke. With a focus on affordability, the parent project aims to develop and integrate a haptic robot into a community-based environment to treat patients with residual cognitive and motor impairments due to stroke. These 1 degree-of-freedom haptic robots apply torques via novel end-effector assemblies that can support and facilitate reaching and grasping motor recovery in the upper limb. The parent grant aims to plans to leverage single and grouped haptic robots and serious gaming to dynamically adjust and personalize therapy for patients presenting along motor and cognitive impairment spectrums. There are four proposed treatment groups based on patient functional behavior: low cognitive/low motor, moderate cognitive/low motor, low cognitive/moderate motor, and moderate cognitive and moderate motor. The parent grant focuses primarily on quantifying changes in patient functional behavior without connecting these changes to neural substrates that may underpin motor and cognition. This diversity supplement will focus on training a talented pre-doctoral student to develop novel algorithms that can support the community-based application of the robot systems. In the community-based rehabilitation setting and nursing homes, there is often limited chances to use brain imaging to help target treatment. Imaging platforms are typically expensive and therefore clinicians rely on only functional behavior to determine treatment direction. A computed tomography (CT or CAT) scan allows doctors to see inside the brain and is often an extremely affordable imaging method that can provide insight into the brain state after stroke. The goal is to leverage this technology to create predictive algorithms that can support personalization of our robot-assisted treatment based on the potential impact of lesion parameters on motor and cognitive function.

项目概要 由于中风是全世界残疾的主要原因，因此需要改善当前的康复护理。 此外，护理负担很重，许多发展中国家没有资源 治疗中风患者所必需的。母项目以负担能力为重点，旨在开发和 将触觉机器人集成到基于社区的环境中，以治疗残存认知和运动的患者 因中风造成的损伤。这些 1 自由度触觉机器人通过新颖的末端执行器施加扭矩 可以支持并促进上肢到达和抓握运动恢复的组件。家长 赠款旨在计划利用单个和分组触觉机器人和严肃的游戏来动态调整和 为患有运动和认知障碍的患者提供个性化治疗。有四个 根据患者功能行为提出的治疗组：低认知/低运动、中度 认知/低运动、低认知/中度运动、中度认知和中度运动。家长 资助主要侧重于量化患者功能行为的变化，而不将这些变化联系起来 可能支持运动和认知的神经基质。 这种多样性补充将重点培养有才华的博士前学生开发新颖的 可以支持机器人系统的社区应用的算法。在以社区为基础的 康复机构和疗养院，使用脑成像来帮助目标的机会通常有限 治疗。成像平台通常很昂贵，因此临床医生仅依靠功能行为来 确定治疗方向。计算机断层扫描（CT 或 CAT）扫描使医生能够看到大脑内部 它通常是一种非常经济实惠的成像方法，可以深入了解中风后的大脑状态。 目标是利用这项技术来创建预测算法，以支持我们的个性化 基于病变参数对运动和认知功能的潜在影响的机器人辅助治疗。