A Critical Analysis of Human-Subject Experiments in Virtual Reality and 3D User Interfaces

Designing usable and effective 3D User Interfaces and 3D Interaction Techniques is very challenging for Virtual Reality system developers and human factors specialists. Indeed, time consuming empirical evaluation is necessary to have an idea about the goodness of the 3D User Interface (3DUI) and the 3D Interaction Technique (3DIT) at the end of their development lifecycle. This may induce a huge loss of time if the result appears not to be satisfying in the end. Moreover, 3DUI evaluation is much more complex than 2D User Interfaces evaluation which is due to heterogeneous Virtual Reality (VR) devices and 3DIT. The aim of this work is to provide a framework allowing developers and experimenters to quickly evaluate 3DUIs and 3DITs during the design and the development lifecycle. The proposed framework is divided into two tools. The first one enables to create an evaluation protocol based on a knowledge database using two data mining algorithms, the "C4.5" to avoid from impossible combinations between devices and indicators and the "Spv Assoc Tree" to build a decision tree between indicators and factors. The second tool of the framework is an Evaluation Virtual Environment (EVE) to perform the evaluation according the protocol created with the first tool.

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Exploring Button Designs for Mid-air Interaction in Virtual Reality: A Hexa-metric Evaluation of Key Representations and Multi-modal Cues

Proceedings of the ACM on Human-Computer Interaction ◽

10.1145/3457141 ◽

2021 ◽

Vol 5 (EICS) ◽

pp. 1-26

Author(s):

Carlos Bermejo ◽

Lik Hang Lee ◽

Paul Chojecki ◽

David Przewozny ◽

Pan Hui

Keyword(s):

Virtual Reality ◽

User Interfaces ◽

Physical Environment ◽

Fundamental Issue ◽

Haptic Cues

The continued advancement in user interfaces comes to the era of virtual reality that requires a better understanding of how users will interact with 3D buttons in mid-air. Although virtual reality owns high levels of expressiveness and demonstrates the ability to simulate the daily objects in the physical environment, the most fundamental issue of designing virtual buttons is surprisingly ignored. To this end, this paper presents four variants of virtual buttons, considering two design dimensions of key representations and multi-modal cues (audio, visual, haptic). We conduct two multi-metric assessments to evaluate the four virtual variants and the baselines of physical variants. Our results indicate that the 3D-lookalike buttons help users with more refined and subtle mid-air interactions (i.e. lesser press depth) when haptic cues are available; while the users with 2D-lookalike buttons unintuitively achieve better keystroke performance than the 3D counterparts. We summarize the findings, and accordingly, suggest the design choices of virtual reality buttons among the two proposed design dimensions.

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Development of a Virtual Reality Simulator for an Intelligent Robotic System Used in Ankle Rehabilitation

Sensors ◽

10.3390/s21041537 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1537

Author(s):

Florin Covaciu ◽

Adrian Pisla ◽

Anca-Elena Iordan

Keyword(s):

Virtual Reality ◽

Muscle Activity ◽

Human Subject ◽

Robotic System ◽

Virtual Reality Simulator ◽

Robotic Rehabilitation ◽

Rehabilitation Process ◽

Leg Muscles ◽

Ankle Rehabilitation ◽

And Control

The traditional systems used in the physiotherapy rehabilitation process are evolving towards more advanced systems that use virtual reality (VR) environments so that the patient in the rehabilitation process can perform various exercises in an interactive way, thus improving the patient’s motivation and reducing the therapist’s work. The paper presents a VR simulator for an intelligent robotic system of physiotherapeutic rehabilitation of the ankle of a person who has had a stroke. This simulator can interact with a real human subject by attaching a sensor that contains a gyroscope and accelerometer to identify the position and acceleration of foot movement on three axes. An electromyography (EMG) sensor is also attached to the patient’s leg muscles to measure muscle activity because a patient who is in a worse condition has weaker muscle activity. The data collected from the sensors are taken by an intelligent module that uses machine learning to create new levels of exercise and control of the robotic rehabilitation structure of the virtual environment. Starting from these objectives, the virtual reality simulator created will have a low dependence on the therapist, this being the main improvement over other simulators already created for this purpose.

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