Prototype Biofeedback Augmented Reality Glasses for Workload Detection with Machine Learning: A Preliminary Study

Abstract

Augmented reality (AR) technology has shown great promise for its ability to seamlessly integrate into the real world and simulated environments. Commercially available headsets offer great functionality for tasks ranging from gaming to productivity. However, the main limitation that these headsets have is that they are bulky, cause visual strain, and being in mixed reality causes some to experience motion sickness-like symptoms. Therefore, we set an objective of this study as to design prototype AR glasses to detect physical workload in real time using a machine learning algorithm. The glasses are made from low-cost, commercially available components that emphasize ergonomics while maintaining functionality. Preliminary results from our pilot study shows that visual strain, bulkiness, and simulator sickness are all decreased when using the prototype AR glasses as compared to the Meta Quest Pro.