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虚拟现实游戏玩法分类说明了视觉空间忽视的多维度性。

Virtual reality gameplay classification illustrates the multidimensionality of visuospatial neglect.

作者信息

Painter David R, Norwood Michael F, Marsh Chelsea H, Hine Trevor, Woodman Christie, Libera Marilia, Harvie Daniel, Dungey Kelly, Chen Ben, Bernhardt Julie, Gan Leslie, Jones Susan, Zeeman Heidi

机构信息

The Hopkins Centre, Menzies Health Institute Queensland, Griffith University, Nathan, Queensland, 4111, Australia.

School of Applied Psychology, Griffith University, Gold Coast, Queensland, 4215, Australia.

出版信息

Brain Commun. 2024 May 3;6(4):fcae145. doi: 10.1093/braincomms/fcae145. eCollection 2024.

Abstract

Brain injuries can significantly impact mental processes and lead to hidden disabilities not easily detectable. Traditional methods for assessing these impacts are imprecise, leading to unreliable prevalence estimates and treatments with uncertain effectiveness. Immersive virtual reality has shown promise for assessment, but its use as a standalone tool is rare. Our research focused on developing and validating a standalone immersive virtual reality classification system for unilateral spatial neglect, a condition common following brain injury characterized by inattention to one side of space. Our study involved 51 brain injury inpatients and 30 controls, all engaging with 'The Attention Atlas', an immersive virtual reality game for testing visual search skills. Our classification system aimed to identify patients with neglect, 'minor atypicality' (indicative of inattention not consistent enough to be labelled as neglect) or non-neglect. This categorization was based on a simple mathematical definition, utilizing gameplay to describe spatial orientation (to the left or right side) and attentional challenge (indicative of search inefficiency). These metrics were benchmarked against a normative model to detect atypical visual search, which refers to gameplay beyond the usual bounds. The combination of neglected side, orientation and challenge factors was used to categorize neglect. We discovered a strong correlation between atypical visual search patterns and neglect risk factors, such as middle cerebral artery stroke, parietal injuries and existing neglect diagnoses (Poisson regression incidence rate ratio = 7.18, 95% confidence interval = 4.41-11.90). In our study, immersive virtual reality-identified neglect in one-fourth of the patients ( = 13, 25.5%), minor atypicality in 17.6% ( = 9) and non-neglect in the majority, 56.9% ( = 29). This contrasts with standard assessments, which detected neglect in 17.6% ( = 9) of cases and had no intermediate category. Our analysis determined six categories of neglect, the most common being left hemispace neglect with above-median orientation and challenge scores. Traditional assessments were not significantly more accurate (accuracy = 84.3%, = 0.06) than a blanket assumption of non-neglect. Traditional assessments were also relatively insensitive in detecting immersive virtual reality-identified neglect (53.8%), particularly in less severe cases and those involving right-side inattention. Our findings underline the effectiveness of immersive virtual reality in revealing various dimensions of neglect, surpassing traditional methods in sensitivity and detail and operating independently from them. To integrate immersive virtual reality into real-world clinical settings, collaboration with healthcare professionals, patients and other stakeholders is crucial to ensure practical applicability and accessibility.

摘要

脑损伤会对心理过程产生重大影响,并导致不易察觉的隐性残疾。评估这些影响的传统方法并不精确,导致患病率估计不可靠,治疗效果也不确定。沉浸式虚拟现实已显示出评估的潜力,但其作为独立工具的使用却很少见。我们的研究重点是开发和验证一种用于单侧空间忽视的独立沉浸式虚拟现实分类系统,单侧空间忽视是脑损伤后常见的一种情况,其特征是对空间的一侧不注意。我们的研究涉及51名脑损伤住院患者和30名对照组人员,他们都参与了《注意力地图集》,这是一款用于测试视觉搜索技能的沉浸式虚拟现实游戏。我们的分类系统旨在识别出患有忽视症、“轻微非典型性”(表明注意力不集中程度不足以被归类为忽视症)或无忽视症的患者。这种分类基于一个简单的数学定义,利用游戏玩法来描述空间方向(向左或向右)和注意力挑战(表明搜索效率低下)。这些指标以一个规范模型为基准,以检测非典型视觉搜索,即超出正常范围的游戏玩法。被忽视侧、方向和挑战因素相结合用于对忽视症进行分类。我们发现非典型视觉搜索模式与忽视风险因素之间存在很强的相关性,如大脑中动脉中风、顶叶损伤和现有的忽视症诊断(泊松回归发病率比 = 7.18,95%置信区间 = 4.41 - 11.90)。在我们的研究中,沉浸式虚拟现实识别出四分之一的患者( = 13,25.5%)患有忽视症,17.6%( = 9)有轻微非典型性,大多数(56.9%, = 29)无忽视症。这与标准评估形成对比,标准评估在17.6%( = 9)的病例中检测出忽视症,且没有中间类别。我们的分析确定了六种忽视症类别,最常见的是左半空间忽视,其方向和挑战得分高于中位数。传统评估并不比一概假设无忽视症更准确(准确率 = 84.3%, = 0.06)。传统评估在检测沉浸式虚拟现实识别出的忽视症方面也相对不敏感(53.8%),尤其是在不太严重的病例以及涉及右侧注意力不集中的病例中。我们的研究结果强调了沉浸式虚拟现实在揭示忽视症的各个方面的有效性,在敏感性和细节方面超越了传统方法,并且可以独立于传统方法运行。为了将沉浸式虚拟现实整合到实际临床环境中,与医疗保健专业人员、患者和其他利益相关者合作对于确保实际适用性和可及性至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dd1/11333965/3ff86a654f16/fcae145_ga.jpg

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