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

I-Corps：开发一种眼球追踪算法，用于评估抑郁、焦虑和其他神经损伤的变化

• 批准号: 2245634
• 负责人: Maarten Lansberg
• 金额: $ 5万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2245634&HistoricalAwards=false
• 关键词: Corps; Developing; eye; tracking; algorithm

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.

这个I-Corps项目的更广泛的影响/商业潜力是开发一种全面的通信检测解决方案，使用眼动跟踪，用于因中风等神经损伤而失去通信的患者。沟通能力的丧失也可能伴随着运动控制的丧失，随之而来的是社交互动的减少和抑郁。这样的患者有再次中风或其他神经损伤的高风险。对于使用纸笔测试作为诊断和康复标准实践的语言病理学家来说，没有单一的解决方案。尽管老年人的这些交流障碍是一种慢性疾病，需要任何解决方案来不断适应他们的需要，但在后续行动中也没有提供监测或心理健康帮助。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持续上传和监控进度。这项技术的目标是利用眼动追踪为护理人员和患者之间提供一个沟通平台，增加社交互动，减少抑郁症。此外，所提出的眼睛跟踪算法可以向提供者提供精神和身体进步以及检测下一次中风。未来的迭代可能会减少这一人群每年40亿美元的医疗费用。这个I-Corps项目是基于眼动跟踪算法的开发，以评估抑郁，焦虑和其他神经损伤的变化。 所提出的技术利用Apple® AR套件中可用的现有眼动跟踪技术来优化标准化刺激（图片和文字）的数字捕获和传递到另一个设备，并将度量用于检测算法。所提出的方法可以针对两种环境场景进行优化：急性住院患者设置和门诊/家庭设置。一个原型正在开发中，以测试这种方法的检测和跟踪用户的凝视向量的对象识别的临床刺激单独为每个病人。 此前，眼动追踪技术已被用于检测创伤性脑损伤。 目标是将凝视信息与所有其他可用的数据源（提供的刺激，来自先前访问的信息，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。 融合的特征然后将用于识别所需的“感兴趣的事件/状态”，其被定义为用于决策系统中的预测的任何事件或条件。使用该技术的飞行员和患者数据可以为语言病理学家提供一种全面的方法，可以进行沟通，监测和检测。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。