Quantifying and Reducing Motor Compensation After Stroke in Ambient Settings

在环境设置中量化和减少冲程后的电机补偿

• 批准号: 9099369
• 负责人: Dustin L. Crouch
• 金额: $ 34.9万
• 依托单位: UNIVERSITY OF TENNESSEE KNOXVILLE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9099369
• 关键词: Academic Research Enhancement Awards; Activities of Daily Living; Affect; Algorithms; Behavior; Biofeedback; Chronic; Clinical; Coupling; Data; Decision Support Model; Decision Trees; Depressed mood; Eating; Elbow; Environment; Evolution; Exhibits; Experimental Designs; Feedback; Financial compensation; Frequencies; Home environment; Independent Living; Individual; Injury; Injury compensation; Intervention; Knowledge; Laboratories; Lead; Learning; Life; Limb structure; Methodology; Modality; Modeling; Monitor; Motion; Motor; Movement; Neurologic; Outcome; Pain; Paralysed; Paresis; Participant; Patients; Pattern; Performance; Persons; Process; Psyche structure; Psychological reinforcement; Quality of life; Recovery; Rehabilitation therapy; Research; Research Design; Role; Self Care; Shoulder; Side; Sterile coverings; Stroke; Supervision; System; Techniques; Time; To specify; United States; Upper Extremity; Work; arm; base; chronic stroke; computerized tools; disability; functional outcomes; graduate student; hemiparesis; hemiparetic stroke; human subject; improved; kinematics; knowledge of results; light weight; motor control; motor learning; novel; post stroke; prospective; public health relevance; sensor; stroke recovery; theories; therapy design; undergraduate student; wearable technology

 DESCRIPTION (provided by applicant): This project will develop a lightweight, unobtrusive system of wearable sensors capable of monitoring an individual's motion in the home setting, and providing real-time feedback of motion quality. This system will help clinicians monitor changes in functional ability in home settings, and will help patients with neuro-motor deficits t take a more active role in self-care. Such a system is particularly useful for determining if individuals are using compensatory motions after stroke. Compensation describes the use of new limbs and strategies to accomplish tasks previously performed with the stroke affected limb. Such compensation is thought to be maladaptive and may lead to further injury and depressed quality of life. Compensatory strategies likely evolve and are affirmed in the absence of a clinical observer (e.g., at home). Thus, this project aims to (1) develop a technique for quantifying such compensation in the home setting using wearable sensors and (2) evaluate the relative efficacy of two biofeedback-based interventions designed to reduce the use of compensatory strategies at home. These interventions provide the participant with feedback regarding their movement quality, but differ in the style of delivery - one provides internally directed feedback regarding the person's body, and the other provides externally directed feedback regarding the person's environment. If successful, this project may benefit many of the seven million people living with chronic stroke in the United States. Our methodology will utilize a prospective experimental design, and a between-groups human subjects study. We anticipate that both biofeedback based interventions will benefit the participant, but that the internally directed feedback will significantly reduce the use of compensation. The methodology developed and validated in this project may eventually benefit other individuals living with chronic motor deficits.

 描述（由申请人提供）：该项目将开发一个轻量级的，不显眼的可穿戴传感器系统，能够监测个人在家庭环境中的运动，并提供运动质量的实时反馈。该系统将帮助临床医生监测家庭环境中功能能力的变化，并将帮助神经运动缺陷患者在自我护理中发挥更积极的作用。这样的系统对于确定个体在中风后是否正在使用补偿运动特别有用。补偿描述了使用新肢体和策略来完成之前使用中风受影响肢体执行的任务。这种补偿被认为是适应不良的，可能导致进一步的伤害和生活质量下降。补偿策略可能会在没有临床观察者的情况下发展和确定（例如，在家）。因此，该项目旨在（1）开发一种使用可穿戴传感器在家庭环境中量化这种补偿的技术，以及（2）评估两种旨在减少在家使用补偿策略的生物反馈干预措施的相对有效性。这些干预为参与者提供关于他们的运动质量的反馈，但是在传递方式上不同-一种提供关于人的身体的内部定向反馈，而另一种提供关于人的环境的外部定向反馈。如果成功，这个项目可能会使美国700万慢性中风患者中的许多人受益。我们的方法将采用前瞻性实验设计和组间人类受试者研究。我们预计，这两种基于生物反馈的干预措施都将使参与者贝内，但内部指导的反馈将大大减少补偿的使用。在这个项目中开发和验证的方法可能最终使其他患有慢性运动缺陷的人贝内。

项目成果

Classifying Unimanual and Bimanual Upper Extremity Tasks in Individuals Post-Stroke

• DOI: 10.1109/embc46164.2021.9629885
• 发表时间: 2021-11
• 期刊: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
• 作者: Aaron Miller;Eric Wade

Comparison of Machine Learning approaches for Classifying Upper Extremity Tasks in Individuals Post-Stroke.

对中风后个体上肢任务进行分类的机器学习方法的比较。

• DOI: 10.1109/embc44109.2020.9176331
• 发表时间: 2020
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Miller,Aaron;Quinn,Lori;Duff,SusanV;Wade,Eric
• 通讯作者: Wade,Eric