Interactive 3D Digital Environments as Ergonomic Data Collection Platforms: A Cross-Immersion Analysis

Abstract

Interactive 3D digital environments have evolved from mere representation media into multifunctional platforms for collecting granular ergonomic and behavioral data. While previous reviews established a foundation for behavior mapping in immersive virtual environments, the rapid emergence of diverse interaction modalities and the integration of multimodal sensing in recent years necessitate a systematic update. This study reviews 208 journal papers from the Web of Science Core Collection (2023–2026) and employs a large language model (DeepSeek V4-Pro) for structured metadata extraction. The analysis compares five data collection categories (physiological, spatiotemporal, foreground interaction, subjective feedback, and contextual data) and eight ergonomic issue classes across four immersion modalities: mobile apps, screen-based open worlds, augmented reality (AR), and immersive virtual reality (VR). The results indicate that immersive VR remains the dominant modality (75.1%) for high-fidelity physiological measurement and cognitive workload analysis, particularly through integrated eye tracking. Screen-based open worlds demonstrate relative efficiency in spatial behavior tracking, while AR presents a balanced profile between interaction usability and physical risk assessment. Mobile apps, by contrast, remain underexplored with only sporadic publications. The cross-modality comparison of ergonomic issues further reveals a clear alignment between immersion level and research focus: lower-immersion modalities concentrate on spatial behavior and HCI, whereas higher-immersion platforms enable comprehensive physiological and cognitive monitoring. Meanwhile, this study demonstrates the feasibility of LLM-assisted information extraction for longitudinal ergonomic research. The findings offer a decision-making guide for selecting appropriate interactive 3D platforms based on specific ergonomic research objectives.

Keywords: 3D Digital Environments, Virtual Reality, Ergonomic Data, Human-space Interaction, Large Language Model

DOI: 10.54941/ahfe1007670