Physical Human Factor Parameters through VR Leisure Contents: Focused on Motion Feature Extraction for Adults from VR Bowling

Abstract

This study explores the impact of Virtual Reality (VR) on leisure sports, focusing on the analysis of motion data in VR bowling among adults aged 19-38. Acknowledging the gap in research regarding physical movement characteristics in VR sports, this work aims to contribute to the ergonomic development of VR leisure content for diverse generations. Using the Vive Pro Eye HMD, Vive Tracker 3.0, and the C2 Plus omnidirectional VR treadmill, we captured detailed three-dimensional position and velocity data. The Unity software facilitated motion data collection, while Python was employed for the analysis, particularly concentrating on the velocity features of the dominant hand controller. The analysis revealed that the Z component of velocity reached its highest mean linear speed at 6.474 during the release phase, aligning with the dynamics of traditional bowling yet underscoring VR's distinctive experience. Conclusively, the findings highlight VR's potential to enrich leisure sports, urging broader research across various VR sports contents and demographics. This pursuit is vital for understanding biomechanical and physical human factors in VR, paving the way for technologies that mitigate generational physical differences and foster the development of accessible, enjoyable VR leisure content for all ages.

Keywords: Human Factor, Motion Data Analysis & Extraction, VR Leisure Sport

DOI: 10.54941/ahfe1004992