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

这个I-Corps项目更广泛的影响/商业潜力是眼动跟踪技术的开发，该技术能够远程评估脑损伤、认知和发育状况以及学习障碍。 据估计，50%的脑震荡未经治疗或未被诊断，这可能会对健康造成严重后果。所提出的技术和测试系统可以由患者在家中定期使用，或者它可以在副业上或在训练设施中用作快速评估，允许训练者或医生利用数据进行快速决策。对于需要深入评估的情况，所提出的系统还可以用于执行一组测试，这些测试捕获患者的眼部反应状态。然后，医生可以通过各种可视化来分析数据并决定适当的治疗。 此外，该系统可以用于递送用于创伤和压力管理的远程治疗会话（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，以及使患者更了解可能变得更严重的状况（例如，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跟踪和机器学习算法来更准确地跟踪面部特征和学生，以进行脑震荡和其他评估。 初步验证测试表明，该技术可以在距离屏幕50厘米的范围内准确跟踪眼球运动。为了增强该技术，开发了一种专有的信号处理和优化算法，以改善信号采集，并实现对用户在屏幕上观看的点（凝视点）处的重要眼睛特征的“零拍摄”检测。采集部件可以与刺激系统组合以提示被检查的人的眼科任务和其他任务。一旦数据被获取，或者由终端用户（例如，患者、父母或教练）或医生/技术人员，可以在设备上分析和可视化信息（例如，膝上型计算机或平板计算机）用于即时反馈，存储在集中式系统中，或者与远程利益相关者传输或共享（即，医生或运动教练）。 此外，所提出的技术可以并入具有内置网络摄像头的大多数便携式设备中，例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由医疗保健提供者执行的在线办公室访问工具一起使用。 数据采集可以与数据分析分离，从而使得终端用户（例如，该奖项反映了NSF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.