Myoelectric Computer Interface to Reduce Muscle Co-Activation after Stroke
Myoelectric Computer Interface to Reduce Muscle Co-Activation after Stroke
批准号:
8771863
负责人:
Marc W. Slutzky
金额:
$22.58万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-06-01 至 2016-05-31
关键词:
Advanced DevelopmentAmericanAnteriorBiological AssayBrainChronicClinicComputer InterfaceComputersCoupledDataDevelopmentDevicesDoseEquipmentFeedbackFrequenciesFutureGoalsHandImpairmentIndividualIsometric ExerciseJointsKnowledgeLeadLearningMapsModalityMotorMovementMuscleNeuraxisOutcomeOutcome MeasurePatientsQuality of lifeResearchStagingStrokeSurvivorsTestingTherapy Clinical TrialsTorqueTrainingTranslatingTranslationsTriceps Brachii MuscleWolvesarmbasebiceps brachii musclechronic strokeconventional therapydeltoid muscledisabilitydosageeffective therapyfunctional improvementhemiparesisimprovedimproved functioninginjuredinnovationinsightkinematicslearned behaviormotor function improvementmotor impairmentmotor learningnovelpectoralis major musclepublic health relevancestroke therapytherapy designtrapezius muscle
中文摘要
描述(由申请人提供):中风仍然是美国慢性残疾的主要原因,超过一半的中风幸存者尽管接受了常规治疗,但手臂功能仍有持续性损伤。 在这些中风幸存者中,
受损的手臂运动是通常不一起激活的肌肉之间的异常共同激活。 这项研究的长期目标是开发一种新的中风治疗方法,使用一种便宜、便携的设备,通过解耦异常的共同激活肌肉来改善运动功能。 这种疗法是一种肌电计算机接口(MCI),将电肌肉活动映射到计算机游戏中光标的移动上。 这向用户提供了关于一对肌肉的共同激活的直接、详细的反馈。 我们的初步结果表明,MCI训练可以使中风幸存者大大减少目标手臂肌肉对的异常共激活,也可能改善功能。 该建议的目的是确定如何优化解耦肌肉激活转化为功能改善。 我们寻求改善慢性中风幸存者的运动功能,甚至超过我们的初步研究,其中评估了单对肌肉的等长MCI训练。 我们将测试两种不同剂量的训练对运动功能的影响。 我们还将
评估在运动过程中个体肌肉可以解耦的程度,这是一个比等长激活更功能相关的条件。 该提案的具体目标是:1)确定多个肌肉对的等长MCI训练改善功能的程度,以及2)确定多个肌肉对的基于运动的MCI训练改善功能的程度。 这项研究是创新的,因为它应用了关于中风后异常共激活的基本见解,开发了一种廉价便携的新型治疗方式。 此外,它还测试了受伤的中枢神经系统重新获得对特定肌肉对的精确控制的基本能力。 重新获得对单个肌肉的精确控制的能力很重要,因为它应该提高将学习行为转移到功能任务的能力。 这种疗法将广泛影响该领域,因为它可以使广泛的中风幸存者使用。 这包括那些有严重运动障碍的人,他们是最需要新疗法的人。 实现我们的目标将是重要的,因为我们希望它能导致中风后运动受损的有效治疗方法的发展,并为该疗法的初步临床试验奠定基础。 我们估计这种疗法仅在美国就能使至少100万中风幸存者受益。
英文摘要
DESCRIPTION (provided by applicant): Stroke remains the leading cause of chronic disability in the U.S., and more than half of stroke survivors have persistent impairment of arm function despite receiving conventional therapy. In these stroke survivors, a significant cause of
impaired arm movement is abnormal co-activation between muscles that normally do not activate together. The long-term goal of this research is to develop a new therapy for stroke using an inexpensive, easily portable device to improve motor function by decoupling abnormally co-activating muscles. This therapy, a myoelectric computer interface (MCI), maps electrical muscle activity onto movements of a cursor in a computer game. This provides direct, detailed feedback about the co-activation of a pair of muscles to the user. Our preliminary results suggest that training with the MCI allows stroke survivors to greatly reduce abnormal co-activation in the targeted arm muscle pair and may also improve function. The objective of this proposal is to determine how to optimize translation of the decoupled muscle activations into functional improvement. We seek to improve motor function in chronic stroke survivors by even more than in our preliminary studies, which assessed isometric MCI training of a single muscle pair. We will test the effects of two different doses of training on motor function. We will also
assess the extent to which individual muscles can be decoupled during movement, which is a more functionally relevant condition than isometric activation. The specific aims of the proposal are to 1) determine the extent to which isometric MCI training of multiple muscle pairs improves function, and 2) determine the extent to which movement-based MCI training of multiple muscle pairs improves function. The proposed research is innovative because it applies fundamental insight about abnormal co-activation after stroke to develop a novel treatment modality that will be inexpensive and portable. In addition, it tests the fundamental ability of an injured central nervous system to regain precise control over specific pairs of muscles. The ability to regain precise control of individual muscles is important because it should improve the ability to transfer the learned behavior to functional tasks. This therapy will broadly impact the field sinc it can enable use by a wide range of stroke survivors. This includes those with severe motor impairments, who are those most in need of new therapies. Achieving our objective will be significant because we expect it to lead to development of an effective treatment for impaired movement after stroke and set the stage for initial clinical trials of the therapy. We estimate tht this therapy could benefit at least 1 million stroke survivors in the U.S. alone.
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会议论文
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海外基金