Discovery of the Neural Drivers Underlying Injury-Risk Biomechanics
损伤风险生物力学背后的神经驱动因素的发现
基本信息
- 批准号:10404593
- 负责人:
- 金额:$ 17.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-05-15 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAddressAdolescentAdultAffectAnterior Cruciate LigamentAttenuatedBilateralBiofeedbackBiomechanicsBrainCerebellumChildClinicalClinical TrialsCognitiveCoupledDataDegenerative polyarthritisDevelopmentEffectivenessEventFailureFemaleFoundationsHealthHealth Care CostsImmersionImpairmentIncidenceInjuryInstructionInterventionJointsKneeKnee InjuriesKnee jointKnowledgeLaboratoriesLeadLifeLigamentsLower ExtremityMechanicsMedical Care CostsMethodsMissionMotionMotorMovementMusculoskeletal DiseasesNeuraxisNeuronal PlasticityOutcomeOutputPainPatternPersonsPhysical activityPositioning AttributePrevalencePrevention programPrevention strategyProcessPublic HealthPublishingQuality of lifeResearchRestRiskRisk AssessmentRisk FactorsSecondary toSensorySportsStandardizationTechniquesTechnologyTestingTimeTrainingUnited States National Institutes of HealthVisualWorkYouthactive lifestyleanterior cruciate ligament injurybasecingulate cortexcognitive processdisabilityfrontal lobehigh riskhigh risk populationimprovedinjury preventioninnovationinstrumentationjoint loadingkinematicsmortalitymotor controlmotor learningmusculoskeletal injuryneuroimagingneuromuscularneuromuscular trainingneuroregulationnovelphysical inactivitypreventprospectiverelating to nervous systemsimulationtechnology developmenttherapeutic targetvirtual realityvirtual reality environmentvirtual reality simulatorvisual motoryoung adult
项目摘要
1 Project Summary/Abstract
2 Anterior cruciate ligament (ACL) injury is a debilitating condition that results in consistent knee degeneration
3 and reduced physical activity capacity, with cumulative health care costs exceeding several billion dollars per
4 annum. The most common mechanism of ACL injury is without player to player contact (termed non-contact)
5 and secondary to motor coordination errors that result in injurious knee joint loading. As such, the current
6 standard for injury prevention is neuromuscular or movement training to correct resultant specific injury-risk
7 mechanics in controlled settings. However, injury reduction strategies have not achieved sufficient efficacy due
8 to inadequate targeting of central nervous system contributions to the motor errors that may underlie and
9 propagate injury-risk in ecologically valid settings. Our published prospective longitudinal data, and preliminary
10 ecologically valid sport-specific virtual reality data, indicates that sensorimotor brain activity underly ACL injury-
11 risk. Thus, the objective of this application is to determine the brain activity associated with injury-risk motor
12 control in standard and ecologically valid sport-specific virtual reality settings. Our preliminary data inform
13 our central hypothesis that those with injury-risk movement patterns rely on a visual and cognitive-motor neural
14 activation strategy, that is further accentuated in ecologically valid sport virtual reality. The proposed research is
15 innovative because it represents a new and substantial departure from prior work that focused primarily on
16 biomechanical outcomes, to now determine the neural activity propagating injury-risk knee motor control. A key
17 breakthrough of this proposal is the biomechanical instrumentation of knee motor control error in real-time during
18 neuroimaging. The expected outcomes from this observational trial will be the identification of the underlying
19 knee motor control neural activity related to ACL injury-risk biomechanics. Successful completion of the proposed
20 Aims will strategically position us to develop a competitive R01 clinical trial application that assesses novel
21 neuromuscular training to target the neural processes identified by this proposal. Specifically, guided by the
22 neural activation strategies identified herein, we will refine prevention programs using novel biofeedback
23 methods, clinical technologies, and motor learning principles to facilitate adaptive brain function that reduces
24 injury incidence. Thus, avoiding the lifelong pain, osteoarthritis, and physical activity limitations, directly aligning
25 with NIH initiatives to reduce injury and physical inactivity in youth and adults, which is the fourth leading cause
26 of global mortality.
27
28
1项目摘要/摘要
前十字韧带(ACL)损伤是一种导致膝关节持续退行性变的衰弱状态。
3和体力活动能力下降,累计保健费用超过每年数十亿美元
4年。前交叉韧带损伤最常见的机制是没有球员对球员的接触(称为非接触)
5并继发于导致膝关节负荷损伤的运动协调错误。因此,目前的
预防损伤的标准是神经肌肉或运动训练,以纠正由此产生的特定损伤风险。
7控制环境中的机械师。然而,减少伤害的策略并没有取得足够的效果,因为
8由于中枢神经系统对运动错误的作用靶向不足,这可能是
9在生态有效的环境中传播伤害风险。我们公布的前瞻性纵向数据,以及初步的
10个生态有效的运动专用虚拟现实数据表明,感觉运动大脑活动低于前交叉韧带损伤-
11风险。因此,这项应用的目标是确定与损伤风险运动相关的大脑活动。
12在标准和生态有效的特定运动虚拟现实环境中进行控制。我们的初步数据通知
13我们的中心假设是,那些有受伤危险的运动模式的人依赖于视觉和认知运动神经
14激活策略,这在生态有效的体育虚拟现实中得到了进一步的强调。拟议的研究是
15具有创新性,因为它代表着与以前主要专注于
16个生物力学结果,现在来确定神经活动传播损伤的危险膝关节运动控制。一把钥匙
这一建议的突破点是膝关节运动控制误差的实时生物力学仪器
18神经成像。这项观察性试验的预期结果将是确定潜在的
19膝关节运动控制与前交叉韧带损伤危险生物力学相关的神经活动。圆满完成拟议中的
20AIMS将在战略上定位我们开发具有竞争力的R01临床试验应用程序,以评估新的
21神经肌肉训练,以此提议确定的神经过程为目标。具体地说,在
22个神经激活策略,我们将使用新的生物反馈来完善预防计划
23种方法、临床技术和运动学习原则,以促进适应大脑功能的减少
24例伤害发生率。因此,避免了终身疼痛、骨关节炎和体力活动的限制,直接对齐
25美国国立卫生研究院倡议减少青少年和成年人的伤害和缺乏运动,这是第四大原因
全球死亡率的26%。
27
28
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dustin Robert Grooms其他文献
Dustin Robert Grooms的其他文献
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{{ truncateString('Dustin Robert Grooms', 18)}}的其他基金
Neuroplastic Mechanisms for Acquisition and Transfer of Injury-Resistant Movement Patterns Assessed in VR Simulated Sport
VR 模拟运动中评估的抗损伤运动模式的获取和转移的神经可塑性机制
- 批准号:
10437035 - 财政年份:2021
- 资助金额:
$ 17.77万 - 项目类别:
Neuroplastic Mechanisms for Acquisition and Transfer of Injury-Resistant Movement Patterns Assessed in VR Simulated Sport
VR 模拟运动中评估的抗损伤运动模式的获取和转移的神经可塑性机制
- 批准号:
10353471 - 财政年份:2021
- 资助金额:
$ 17.77万 - 项目类别:
Discovery of the Neural Drivers Underlying Injury-Risk Biomechanics
损伤风险生物力学背后的神经驱动因素的发现
- 批准号:
10208101 - 财政年份:2021
- 资助金额:
$ 17.77万 - 项目类别:
Discovery of the Neural Drivers Underlying Injury-Risk Biomechanics
损伤风险生物力学背后的神经驱动因素的发现
- 批准号:
10615762 - 财政年份:2021
- 资助金额:
$ 17.77万 - 项目类别:
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