I-Corps: Eye-Tracking System for Cognitive Abnormalities and Traumatic Brain Injuries

I-Corps项目更广泛的影响/商业潜力是眼动追踪技术的发展，该技术可以远程评估脑损伤、认知和发育状况以及学习障碍。据估计，50%的脑震荡得不到治疗或未得到诊断，这可能对健康造成严重后果。所建议的技术和测试系统可以由患者在家中定期使用，也可以用作场外或培训设施的快速评估，允许培训师或医生利用数据进行快速决策。对于需要深入评估的病例，建议的系统也可用于执行一系列测试，以捕获患者的动眼病反应状态。然后，医生可以通过各种可视化分析数据，并决定适当的治疗方法。此外，该系统可用于提供创伤和压力管理的远程治疗会议（例如，基于双侧刺激的治疗），并将支持在农村和偏远地区提供更好的护理，以及使患者更加了解可能变得更严重的情况（例如，反复脑震荡）。这个I-Corps项目是基于一个应用程序的开发，该应用程序使用网络摄像头眼球追踪和机器学习算法来更准确地跟踪面部特征和瞳孔，以进行脑震荡和其他评估。最初的验证测试表明，该技术可以准确地跟踪距离屏幕50厘米范围内的眼球运动。为了增强这项技术，我们开发了一种专有的信号处理和优化算法，以改进信号采集，并在用户看屏幕的位置（注视点）实现对重要眼睛特征的“零拍摄”检测。获取组件可以与刺激系统相结合，以提示被检查者的动眼肌任务和其他任务。一旦获得数据，无论是由最终用户（如患者、家长或教练）还是由医生/技术人员，信息都可以在设备（如笔记本电脑或平板电脑）上进行分析和可视化以获得即时反馈，存储在集中系统中，或传输或与远程利益相关者（如医生或运动教练）共享。此外，建议的技术可以整合到大多数内置网络摄像头的便携式设备中，如用户已经拥有的笔记本电脑和平板电脑，或者可以与其他脑震荡评估工具和医疗保健提供者进行在线办公室访问的工具一起使用。数据采集可以与数据分析分离，从而使最终用户（例如运动员或医疗保健提供者）能够在比赛或练习期间在家或在场边完成评估。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of eye tracking technology that enables remote assessment of brain injuries, cognitive and developmental conditions, and learning disabilities. It is estimated that 50% of concussions go untreated or undiagnosed, which can have significant health consequences. The proposed technology and testing system may be utilized by patients at home on a regular basis or it may be used as a quick assessment on the sideline or in a training facility allowing the trainers or physicians to utilize data for quick decision making. For cases requiring an in-depth assessment, the proposed system also may be utilized to perform a battery of tests that capture the oculomotor eye response status of the patient. Then, a physician may analyze the data through a variety of visualizations and decide the appropriate treatment. In addition, the system may be used for the delivery of remote therapy sessions for trauma and stress management (e.g., therapy based on bilateral stimulation), and would support delivering better care in rural and remote areas, as well as making patients more aware of conditions that can become more serious (e.g., repeat concussions).This I-Corps project is based on the development of an application that uses webcam eye-tracking and machine learning algorithms to track facial features and the pupils more accurately for concussion and other assessments. Initial validation tests have shown the proposed technology accurately tracks eye movements within 50 centimeters from the screen. To enhance the technology, a proprietary signal processing and optimization algorithm was developed to improve signal acquisition and enable “zero-shot” detection of significant eye features at the point where the user is looking on the screen (gaze point). The acquisition component may be combined with a stimulation system to prompt oculomotor tasks and other tasks for the person being examined. Once data is acquired, either by the end user (e.g., patient, parent, or coach) or by a physician/technician, the information may be analyzed and visualized on the device (e.g., laptop or tablet) for immediate feedback, stored in a centralized system, or transmitted or shared with remote stakeholders (i.e., physicians or athletic trainers). In addition, the proposed technology may be incorporated into most portable devices with built-in webcams such as laptops and tablets that users already possess or may be used alongside other concussion assessment tools and tools for online office visits performed by healthcare providers. Data acquisition may be decoupled from data analysis, thus enabling end users (e.g., athletes or healthcare providers) to complete the assessment at home or on the sideline during a competition or practice.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.