SCH: INT: Reducing Traumatic Brain Injury Risk with Impact Compensation

创伤性脑损伤是美国死亡和残疾的主要原因。每年有超过170万人遭受脑损伤，占急诊室所有受伤人数的三分之一。制定康复和治疗策略来管理这种疾病是很重要的，但预防脑创伤的发生也是解决方案的关键组成部分。该提案的目标是通过智能技术来降低创伤性脑损伤的风险，该技术收集感官数据以实时预测和描述头部撞击，根据这些撞击特征优化保护机制，并将撞击创伤属性发送到临床数据库以进行进一步分析和损伤风险预测。这项技术将大大改善机动车碰撞、运动和工业事故中创伤性脑损伤的预防和诊断。为了实现这一目标，基础研究工作包括：（1）实时情况监测，以预测何时以及如何发生危险的影响;（2）主动预防机制，以降低脑损伤影响的风险。该技术的初步评估是在运动环境中，但系统组件可以广泛适用于机动车辆，工业安全头盔和老年人的生活环境中的实施。本提案的研究目标是：（1）通过先进的情景监测，肌肉骨骼激活和冲击特定力减少来降低创伤性脑损伤的风险;（2）改进基于多尺度脑形变模型的脑损伤潜在风险识别。这些目标是通过整合四个基础研究工作来实现的。首先，跟踪和碰撞检测算法的基础上开发的射频（RF）传感，处理和灵活的天线设计。当与三轴加速度计、陀螺仪和磁力计结合使用时，这些算法提供了检测物体所需的传感能力，捕获周围物体的方向速度数据，并实时处理数据以确定即将发生碰撞的概率和特征。第二，肌肉骨骼紧接着听觉警告的研究，作为一种手段，最大限度地减少头部或身体的影响后的头部角加速度。听觉警告线索和肌肉紧握策略的发展利用运动学肌肉骨骼建模和人类主体研究来确定所需的听觉线索和响应时间以及肌肉激活参数，最好地减轻头部角加速度在碰撞过程中。第三，主动力减少具体即将发生的影响的特点是实施使用一个独特的可折叠充气膀胱。最佳的压力和偏转特性的膀胱的基础上的冲击速度和方向，并评估与一种新的三维多尺度有限元模型的人的头部。第四个基础研究领域是利用多尺度模型研究头部撞击力和加速度与撞击后脑组织局部变形的关系。这些研究将被用来改善从撞击运动学预测TBI的风险。

Traumatic brain injury is a leading cause of death and disability in the United States. Over 1.7million people sustain a brain injury each year and make up one-third of all injuries seen in theemergency room. Developing rehabilitation and treatment strategies to manage this disease areimportant, but preventing the occurrence of brain trauma is also critical component to the solution.The goal of this proposal is to reduce the risk of traumatic brain injury through smart technologythat collects sensory data to predict and characterize head impact in real-time, optimizes protectivemechanisms based on those impact characteristics, and sends impact trauma attributes to a clinicaldatabase for further analysis and injury risk prediction. This technology will substantially improvetraumatic brain injury prevention and diagnosis in motor vehicle crashes, sports, and industrialaccidents. To accomplish this goal, fundamental research efforts include (1) real-time situationalmonitoring to predict when and how dangerous impacts are about to occur and (2) activeprevention mechanisms to reduce the risk of brain injury impact. Initial evaluation of thetechnology is in a sports setting, but the system components can be widely adaptive forimplementation in motor vehicles, industrial safety helmets, and living environments for theelderly.The research goals of this proposal are to (1) reduce the risk of traumatic brain injury throughadvanced situational monitoring, musculoskeletal activation, and impact-specific force reduction;and (2) to improve potential identification of head injury risk based on multiscale braindeformation modeling. These goals are accomplished by integrating four fundamental researchefforts. First, tracking and collision detection algorithms are developed based on radio frequency(RF) sensing, processing, and flexible antenna design. When used in conjunction with triaxialaccelerometers, gyroscopes, and magnetometers, these algorithms provide the sensing capabilitiesrequired to detect objects, capture directional velocity data of surrounding objects, and processdata in real-time to determine probabilities and characteristics of impending collision. Second,musculoskeletal clenching following auditory warning is investigated as a means of minimizinghead angular acceleration following head or body impact. The development of auditory warningcues and muscle clench strategies utilizes kinematic musculoskeletal modeling and human subjectstudies to identify required auditory cues and response times as well as muscle activationparameters that best mitigate head angular acceleration during a collision. Third, active forcereduction specific to impending impact characteristics are implemented using a unique controllableair-filled bladder. Optimal pressure and deflection characteristics of the bladder are based onimpact velocity and direction, and evaluated with a novel three-dimensional multiscale finiteelement model of the human head. This model incorporates anatomical variability in themicrostructures at the brain-skull interface, a region that is critical to predictions of head injury.The fourth fundamental research area uses the multiscale model to investigate the relationship ofhead impact force and acceleration to regional deformation of brain tissue upon impact. Thesestudies will be used to improve predictions of TBI risk from impact kinematics.