Hayes John, Gabbard Joseph L, Mehta Ranjana K
Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States.
Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, United States.
Front Neuroergon. 2025 Apr 28;6:1539552. doi: 10.3389/fnrgo.2025.1539552. eCollection 2025.
INTRODUCTION: Recent advancements in augmented reality (AR) technology have opened up potential applications across various industries. In this study, we assess the effectiveness of psychomotor learning in AR compared to video-based training methods. METHODS: Thirty-three participants (17 males) trained on four selection-based AR interactions by either watching a video or engaging in hands-on practice. Both groups were evaluated by executing these learned interactions in AR. RESULTS: The AR group reported a higher subjective workload during training but showed significantly faster completion times during evaluation. We analyzed brain activation and functional connectivity using functional near-infrared spectroscopy during the evaluation phase. Our findings indicate that participants who trained in AR displayed more efficient brain networks, suggesting improved neural efficiency. DISCUSSION: Differences in sex-related activation and connectivity hint at varying neural strategies used during motor learning in AR. Future studies should investigate how demographic factors might influence performance and user experience in AR-based training programs.
引言:增强现实(AR)技术的最新进展为各个行业开辟了潜在的应用领域。在本研究中,我们评估了与基于视频的训练方法相比,AR中精神运动学习的有效性。 方法:33名参与者(17名男性)通过观看视频或进行实际操作,对四种基于选择的AR交互进行训练。两组都通过在AR中执行这些所学的交互来进行评估。 结果:AR组在训练期间报告的主观工作量较高,但在评估期间完成时间明显更快。我们在评估阶段使用功能近红外光谱分析大脑激活和功能连接。我们的研究结果表明,在AR中训练的参与者表现出更有效的大脑网络,表明神经效率有所提高。 讨论:与性别相关的激活和连接差异暗示了在AR中运动学习期间使用的不同神经策略。未来的研究应该调查人口统计学因素如何影响基于AR的训练计划中的表现和用户体验。
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