将生物反馈和人工智能融入虚拟现实训练场景:系统文献综述

IF 1.5 Q2 EDUCATION & EDUCATIONAL RESEARCH SIMULATION & GAMING Pub Date : 2024-03-14 DOI:10.1177/10468781241236688
Karen L. Blackmore, Shamus P. Smith, Jacqueline D. Bailey, Benjamin Krynski
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引用次数: 0

摘要

背景在模拟培训和严肃游戏中加入生物反馈和人工智能(AI),在提高培训效果方面取得了可喜的成果,可以提高参与度、积极性和信息保留率。本系统性文献综述探讨了将生物反馈和人工智能整合到电子扩展现实(XR)培训场景中的问题,这也是首次对生物反馈和人工智能技术在该领域的应用进行综合概述的综述。方法本综述使用了与生物反馈、人工智能、XR和培训相关的关键词,并纳入了以下论文:包含在XR培训场景中使用生物反馈和人工智能的内容;至少报告了一项与培训效果相关的结果;以英文发表;经过同行评审;日期为2016年1月1日至2022年2月7日。结果结果表明,许多研究使用单个生物传感设备收集两个或多个生物信号。这与应用环境尤为相关,因为在应用环境中,人们希望使用方便且对培训/教育活动的干扰最小。此外,腕带、无线带或头带等轻巧便携的设备也是首选。此外,在 XR 培训中,眼动跟踪、皮肤电活动(EDA)和光敏血压计(PPG)是特别有用的压力和/或认知负荷生物标记。各种机器学习(ML)方法被用于支持 XR 环境中的生物反馈系统。然而,采用生物信号实时分析的研究数量有限(仅占研究的 1%),这表明目前在实施此类系统方面存在挑战。要全面了解生物反馈和人工智能在这些领域使用的 XR 训练场景中的整合潜力,还需要在国防和一般工业等其他领域开展进一步研究。
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Integrating Biofeedback and Artificial Intelligence into eXtended Reality Training Scenarios: A Systematic Literature Review
BackgroundThe addition of biofeedback and artificial intelligence (AI) in simulation training and serious games has shown promising results in improving the effectiveness of training and can lead to increased engagement, motivation, and retention of information. This systematic literature review explores the integration of biofeedback and artificial intelligence into eXtended reality (XR) training scenarios and is the first review to provide a consolidated overview of applied biofeedback and AI technologies in this area.MethodThis review was conducted using keywords related to biofeedback, AI, XR, and training and included papers that: contained the use of biofeedback and AI in XR training scenarios; reported on at least one outcome related to training effectiveness; were published in English; were peer-reviewed; date from 1 January 2016 – 7 February 2022.ResultsThe results indicate that many studies collect two or more biosignals using a single biosensing device. This is particularly relevant in applied settings, where ease of use and minimal interference in training/education activities is desired. Also, that light, portable devices such as wrist bands, wireless straps, or headbands are preferred. Additionally, eye tracking, electrodermal activity (EDA), and photoplethysmograms (PPG) present as particularly useful biomarkers of stress and/or cognitive load in XR training contexts. A wide variety of machine learning (ML) approaches were used to support biofeedback systems in XR environments. However, a limited number of studies employed real-time analysis of biosignals (just 1% of studies) which indicates current challenges in implementing such systems.ConclusionThe majority of papers meeting the selection criteria were from the fields of education and healthcare. Further research in other domains, such as defense and general industry, is needed to gain a comprehensive understanding of the potential for biofeedback and AI integration in XR training scenarios used in these domains.
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来源期刊
SIMULATION & GAMING
SIMULATION & GAMING EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
5.30
自引率
5.00%
发文量
35
期刊介绍: Simulation & Gaming: An International Journal of Theory, Practice and Research contains articles examining academic and applied issues in the expanding fields of simulation, computerized simulation, gaming, modeling, play, role-play, debriefing, game design, experiential learning, and related methodologies. The broad scope and interdisciplinary nature of Simulation & Gaming are demonstrated by the wide variety of interests and disciplines of its readers, contributors, and editorial board members. Areas include: sociology, decision making, psychology, language training, cognition, learning theory, management, educational technologies, negotiation, peace and conflict studies, economics, international studies, research methodology.
期刊最新文献
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