Integration of eye-tracking systems with sport concussion assessment tool 5th edition for mild TBI and concussion diagnostics in neurotrauma: Building a framework for the artificial intelligence era

Augusto Müller Fiedler , Renato Anghinah , Fernando De Nigris Vasconcellos , Alexis A. Morell , Timoteo Almeida , Bernardo de Assumpção , Joacir Graciolli Cordeiro
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Abstract

Traumatic Brain Injuries (TBIs), including mild TBI (mTBI) and concussions, affect an estimated 69 million individuals annually with significant cognitive, physical, and psychosocial consequences. The Sport Concussion Assessment Tool 5th Edition (SCAT5) is pivotal for diagnosing these conditions but possesses inherent subjectivity. Conversely, eye-tracking systems provide objective data, capturing subtle disruptions in ocular and cognitive functions often missed by traditional measures. Yet, the concurrent use of these promising tools for neurotrauma diagnostics is relatively unexplored. This paper proposes integrating eye-tracking with SCAT5 to enhance mTBI and concussion diagnostics. We introduce a model that synergistically combines the strengths of both techniques into an ‘ocular score’, adding objectivity to SCAT5. This union promises improved clinical decision-making, impacting return-to-play, fitness-to-drive, and return-to-work judgments, providing a novel landscape in the neurotrauma scenario. However, our theoretical framework requires empirical validation. We advocate for future large-scale collaborative research databases, and exploration of eye-tracking-based diagnostic markers. Our methodology highlights the potential of this integrated approach to redefine neurotrauma management and diagnostics, addressing a critical global health concern with proven utility in high-risk settings like sports and the military.

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眼动追踪系统与运动脑震荡评估工具第5版的集成,用于轻度TBI和神经创伤脑震荡诊断:构建人工智能时代的框架
创伤性脑损伤(TBI),包括轻度TBI (mTBI)和脑震荡,每年影响约6900万人,造成严重的认知、身体和社会心理后果。运动脑震荡评估工具第5版(SCAT5)是诊断这些条件的关键,但具有固有的主观性。相反,眼球追踪系统提供了客观的数据,捕捉到传统测量方法往往无法捕捉到的眼部和认知功能的细微变化。然而,这些有前途的神经创伤诊断工具的同时使用是相对未被探索的。本文提出将眼动追踪与SCAT5相结合,增强mTBI和脑震荡诊断能力。我们引入了一个模型,将两种技术的优势协同结合到“视觉评分”中,为SCAT5增加了客观性。该联盟有望改善临床决策,影响重返赛场、健康驾驶和重返工作岗位的判断,为神经创伤场景提供新的前景。然而,我们的理论框架需要实证验证。我们提倡未来大规模的合作研究数据库,并探索基于眼动追踪的诊断标记。我们的方法强调了这种综合方法重新定义神经创伤管理和诊断的潜力,解决了一个关键的全球健康问题,并在体育和军事等高风险环境中得到了证实。
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来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
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