Attention deficit hyperactivity disorder (ADHD) is a neurobiological condition that appears during an individual's childhood and may follow her/him for life. The research objective was to understand better how and which computer technologies have been applied to support ADHD diagnosis and treatment. The research used the systematic literature review method: a rigorous, verifiable, and repeatable approach that follows well-defined steps. Six well-known academic data sources have been consulted, including search engines and bibliographic databases, from technology and health care areas. After a rigorous research protocol, 1,239 articles were analyzed. For the diagnosis, the use of machine learning techniques was verified in 61 percent of the articles. Neurofeedback was ranked second with 9.3 percent participation, followed by serious games and eye tracking with 5.6 percent each. For the treatment, neurofeedback was present in 50 percent of the articles, whereas some studies combined both approaches, accounting for 31 percent of the total. Nine percent of the articles reported remote assistance technology, whereas another 9 percent have used virtual reality. By highlighting the leading computer technologies used, their applications, results, and challenges, this literature review breaks ground for further investigations. Moreover, the study highlighted the lack of consensus on ADHD biomarkers. The approaches using machine learning call attention to the probable occurrence of overfitting in several studies, thus demonstrating limitations of this technology on small-sized bases. This research also presented the convergence of evidence from different studies on the persistence of long-term effects of using neurofeedback in treating ADHD.

中文翻译：

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计算机技术在注意力缺陷多动障碍诊断和治疗中的趋势、局限性和挑战

注意缺陷多动障碍 (ADHD) 是一种出现在个人童年时期的神经生物学疾病，可能会伴随她/他一生。研究目标是更好地了解如何以及使用哪些计算机技术来支持 ADHD 的诊断和治疗。该研究使用了系统的文献回顾方法：一种严格、可验证和可重复的方法，遵循明确定义的步骤。已经咨询了来自技术和医疗保健领域的六个知名学术数据源，包括搜索引擎和书目数据库。经过严格的研究方案，对 1,239 篇文章进行了分析。对于诊断，机器学习技术的使用在 61% 的文章中得到了验证。神经反馈以 9.3% 的参与率排名第二，其次是严肃游戏和眼动追踪，各占 5.6%。对于治疗，神经反馈出现在 50% 的文章中，而一些研究结合了这两种方法，占总数的 31%。9% 的文章报告了远程协助技术，而另外 9% 的文章使用了虚拟现实。通过突出使用的领先计算机技术、它们的应用、结果和挑战，这篇文献综述为进一步研究奠定了基础。此外，该研究强调了对 ADHD 生物标志物缺乏共识。使用机器学习的方法引起了人们对在几项研究中可能发生的过度拟合的关注，从而证明了该技术在小型基础上的局限性。