论文标题

基于面部肌电图的自适应虚拟现实游戏,用于认知训练

Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training

论文作者

Reidy, Lorcan, Chan, Dennis, Nduka, Charles, Gunes, Hatice

论文摘要

认知培训显示出有希望的结果,可以改善与注意力,解决问题,阅读理解和信息检索有关的人类认知。但是,认知培训文献中经常被引用的两个问题是缺乏与培训计划的用户参与,以及未发达的技能无法推广到日常生活。本文介绍了一种新的认知训练(CT)范式,旨在通过结合游戏化,虚拟现实(VR)的好处和情感适应性来解决这两个局限性,并在开发引人入胜的,生态有效的CT任务中。此外,它将面部肌电图(EMG)作为确定CT任务时用户影响的一种手段。然后,将这些信息用于在用户玩游戏时动态调整游戏的实时难度,以使他们进入流动状态。通过使用KNN对输入信号的DWT-HAAR近似来,分别为价和唤醒的识别率分别为64.1%和76.2%。然后,通过对照组的老年人评估情感感知的VR认知训练干预措施。获得的结果证明了适应技术可以导致更大的能力感觉和对用户技能的更合适挑战的观念。

Cognitive training has shown promising results for delivering improvements in human cognition related to attention, problem solving, reading comprehension and information retrieval. However, two frequently cited problems in cognitive training literature are a lack of user engagement with the training programme, and a failure of developed skills to generalise to daily life. This paper introduces a new cognitive training (CT) paradigm designed to address these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task. Additionally, it incorporates facial electromyography (EMG) as a means of determining user affect while engaged in the CT task. This information is then utilised to dynamically adjust the game's difficulty in real-time as users play, with the aim of leading them into a state of flow. Affect recognition rates of 64.1% and 76.2%, for valence and arousal respectively, were achieved by classifying a DWT-Haar approximation of the input signal using kNN. The affect-aware VR cognitive training intervention was then evaluated with a control group of older adults. The results obtained substantiate the notion that adaptation techniques can lead to greater feelings of competence and a more appropriate challenge of the user's skills.

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