I-Corps: Developing an eye tracking algorithm that will assess the changes in depression, anxiety and other neurological insults

I-Corps项目更广泛的影响/商业潜力是开发一种全面的通信检测解决方案，使用眼动追踪技术为中风等神经损伤导致的通信丧失患者提供服务。沟通障碍还可能伴随着运动控制能力的丧失，随后是社交活动的减少和抑郁。这类患者再次中风或其他神经损伤的风险很高。对于使用纸笔测试作为诊断和康复的标准做法的语言病理学家来说，没有单一的解决方案。在随访中也没有提供监测或心理健康帮助，尽管老年人的这些沟通障碍是一种慢性疾病，需要不断适应其需求的任何解决方案。预期的主要客户是语言病理学家，他们可以远程访问内容并上传和持续监控进度。这项技术的目标是利用眼动追踪技术为护理人员和患者之间提供一个交流平台，增加社交互动，减少抑郁。此外，所提出的眼动追踪算法可以向提供者提供精神和身体的进展，并检测下一次中风。未来的迭代可能会为这一人群每年减少40亿美元的医疗保健成本。这个I-Corps项目是基于眼动追踪算法的发展来评估抑郁、焦虑和其他神经损伤的变化。拟议的技术利用Apple®AR套件中现有的眼动追踪技术，以优化将标准化刺激（图片和文字）以数字方式捕获和传输到另一个设备，并使用检测算法的指标。这种建议的方法可以优化两种环境情景：急性住院设置和门诊/家庭设置。目前正在开发一个原型来测试这种方法，用于检测和跟踪用户凝视向量，以识别每个患者单独产生的临床刺激。此前，眼动追踪技术已被用于检测创伤性脑损伤。目标是将注视信息与所有其他可用的数据来源（呈现的刺激、以前访问的信息，包括基线结果、自我报告和指导评估，以及专家临床反馈）融合在一起。然后使用融合的特征来识别所需的“感兴趣的事件/状态”，定义为决策系统中用于预测的任何事件或条件。使用该技术的试点和患者数据可以为语言病理学家提供一种全面的方法，允许交流，监测和检测。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 a comprehensive communication-detection solution using eye tracking for patients with communication loss due to neurological insults like stroke. Communication loss also can be accompanied by loss of motor control, followed by decrease in social interaction and depression. Such patients are at high risk for another stroke or other neurological insults. There is no single solution available to the speech pathologists who use paper-pencil tests as standard practice for diagnosis and rehabilitation. There is also no monitoring or mental health help provided at follow-up despite the fact that these communication disorders in older adults are a chronic condition and require any solution to be continuously adapted to their needs. The intended primary customers are speech pathologists who can remotely access the content and upload and monitor progress continuously. The goal of the proposed technology is to use eye tracking to provide a communication platform between caregiver and patient, increasing social interaction and reducing depression. In addition, the proposed eye-tracking algorithm may provide mental and physical progress to the provider as well as detect the next stroke. Future iterations may reduce the $4 billion healthcare costs per year in this population.This I-Corps project is based on the development of an eye tracking algorithm to assess the changes in depression, anxiety, and other neurological insults. The proposed technology utilizes existing eye tracking technology available in the Apple® AR kit to optimize the capture and delivery of standardized stimuli (pictures and words) digitally to another device, and use the metrics for the detection algorithm. This proposed method may be optimized for two environmental scenarios: acute in-patient settings and outpatient/in-home settings. A prototype is under development to test this method for detection and tracking of user gaze vectors for object recognition for clinical stimuli generated individually for each patient. Previously, eye tracking technology has been tested for detection of traumatic brain injury. The goal is to fuse gaze information with all other available sources of data (stimuli presented, information from previous visits including baseline results, self-report and guided assessments, and expert clinical feedback). Fused features will then be used to recognize a required “event/state of interest" defined as any event or condition that is used for prediction in the decision system. Pilot and patient data using this technology may provide a comprehensive method for speech pathologists that allows communication, monitoring and detection.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.