As the development of augmented reality (AR) and virtual reality (VR) applications is still limited to those with substantial amounts of technical knowledge, the prototyping and testing of user interface (UI) designs for AR and VR applications remotely proves difficult. Recent tools proposed for prototyping AR/VR applications focus on working toward increased fidelity of prototyping methods, but provide limited ability to easily collect objective quantitative data from user interactions with prototypes, especially in remote settings. In this paper, we present a remote usability study using Adobe XD rapid prototyping software integrated with Maze User Testing Software, that collect data for UI designs for an existing cross-platform software. The results were found by collecting task completion time, misclick rate, and user click-data using heatmaps. We discuss the results of our study, and show that objective quantitative data can be collected for AR/VR prototypes in remote testing settings to provide insightful usability feedback in early stages of interface design.

While researchers have found benefits in the use of Augmented Reality (AR) for training in maintenance tasks, many existing applications are limited to the use of hand-held controllers for interaction with the virtual environment. One novel alternative to traditional controls is the use of Brain-Machine Interface (BMI) systems and Motor Imagery (MI), using data from the user’s brain in the form of electroencephalography (EEG) waves. While some research has explored the use of BMI with virtual environments, the use of MI in an AR system has not been explored for use in training how to accomplish a procedural task. Therefore, this paper presents a BMI system combined with AR, to create a framework that allows for hands-free traversal of a predefined instruction-set for training using user brain activity. The created prototype allows for control of an AR environment using three modalities: brain activity, voice commands, and hand gestures. The created BMI-AR prototype allows for control of navigation through a predetermined instruction set using a user’s brain waves or voice commands, as well as allow users to see their passive EEG readings of affective mental state in real time. The initial prototype resulted in promising initial machine learning (ML) accuracy scores for motor imagery (MI) tasks.

This paper presents a virtual reality (VR) application that allows users to view a series of 360 degree videos, depicting bystander intervention scenarios, from a bystander perspective. Bystander intervention is a commonly used training on how to prevent and de-escalate potentially harmful or violent scenarios [5]. This application enables users to witness, from a first-hand perspective, a successful bystander intervention strategy being used by another person. This paper discusses motivations for creating such an application by giving an overview of the state of the art in bystander intervention training methods. It also discusses the application flow and design of the created system. Additionally, a preliminary user study was conducted to gain initial feedback and user perspectives on the system.