混合现实游戏中用户粘性的神经生理学相关性

IF 3.8
F Garro, E Fenoglio, M Laffranchi, N Garcia-Hernandez, M Semprini
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引用次数: 0

摘要

目的:本研究探讨基于混合现实(MR)的运动游戏中上肢运动中用户参与度(UE)的神经生理学相关因素。该研究探讨了MR环境对大脑活动的调节是否与传统运动不同,以及物理物体的相互作用是否会影响参与。方法:记录了15名健康成人在四种条件下(有和没有MR和物理物体的相互作用)进行双侧手臂运动的高密度脑电图(EEG)。参与指数是从预定义皮质区域的源级和传感器级的光谱特征(θ、α和它们的比值)中得出的。时间过程动态和主观用户体验也进行了评估。主要结果:与非mr条件相比,基于mr的游戏显著提高了theta功率,降低了alpha功率,表明更大的认知和注意力投入。这些影响在额叶、感觉运动和顶叶区域是一致的,并且随着时间的推移保持稳定。物理对象互动对参与没有显著影响。主观上,磁共振条件在刺激、效率和新颖性方面被评为更高。意义:磁共振在康复中的有效性取决于持续的用户参与度,这通常通过主观问卷来评估。这项研究表明,脑电图衍生的指标——尤其是θ和α活动——客观地反映了参与度。这些结果支持EEG作为开发适应性脑响应康复技术的实时监测工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neurophysiological correlates of user engagement in mixed reality exergames.

Objective.This study investigates the neurophysiological correlates of user engagement (UE) during upper-limb exercises in mixed reality (MR)-based exergames. It explores whether MR environments modulate brain activity differently than traditional exercises and whether physical object interaction affects engagement.Methods.High-density electroencephalography (EEG) was recorded from fifteen healthy adults performing bilateral arm exercises under four conditions-with and without MR and physical object interaction. Engagement indices were derived from spectral features (theta, alpha, and their ratios) at both source- and sensor-levels across predefined cortical regions. Time-course dynamics and subjective user experience were also evaluated.Main results.MR-based exergames significantly increased theta power and decreased alpha power compared to non-MR conditions, indicating greater cognitive and attentional engagement. These effects were consistent across frontal, sensorimotor, and parietal regions and remained stable over time. Physical object interaction had no significant effect on engagement. Subjectively, MR conditions were rated higher in stimulation, efficiency, and novelty.Significance.The effectiveness of MR in rehabilitation depends on sustained UE, which is typically assessed through subjective questionnaires. This study demonstrates that EEG-derived metrics-particularly theta and alpha activity-objectively reflect engagement. These results support EEG as a real-time monitoring tool for developing adaptive, brain-responsive rehabilitation technologies.

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