The commercialization of virtual reality (VR) platforms has enabled and increased interest in the use of VR for social activities. Users are now able to enjoy a shared experience with others in an immersive social VR environment. However, current methods for designing and measuring shared user experience (UX) have been insufficient. To design and measure VR UX in a consistent manner, it is essential to develop design guidelines and evaluation tools focusing on user interfaces and interactions. In this study, a new evaluation tool that can comprehensively evaluate VR is proposed, and its validity and reliability were verified. In addition, user tasks and activities in VR were defined for a variety of users, and VR scenario guidelines were developed. Finally, the difference in UX according to device type (PC vs. HMD) was identified. This study is expected to be useful for developing social VR scenarios and evaluation tools.

This study aims to understand the usability of common button colours and background choices in the existing augmented reality (AR) interface. AR is increasingly used in dynamic situations, such as driving using an AR head-up display. However, studies regarding the usability of AR interfaces, especially about the colours, are scarce. Twenty-four participants performed button selection tasks in an experiment using Microsoft HoloLens. Three measures (task completion time, the number of errors, and button colour visibility were collected for the 12 experimental conditions (3 backgrounds by 4 button colours). Significant differences were found in completion time between backgrounds and blue button visibility. On a moving background, the most effective button colour is orange, and the most minor effective button colour is blue. The results of this study can be used for colour choices in designing AR applications and devices.

ABSTRACT Augmented reality (AR) technologies are becoming increasingly popular. However, studies regarding the usability of AR interfaces are scarce. This study aims to derive the optimal usability design of the AR interface by analyzing the performance of 12 interface conditions (2 button sizes × 3 distances × 2 interaction types). An experiment was conducted using Microsoft HoloLens, in which participants performed button selection tasks with an array of 3 × 3 virtual buttons. The task completion time and the number of errors were measured along with a subjective satisfaction score. The results showed that a clicker-based interaction was more effective in task completion time, the number of errors and user satisfaction than a hand gesture. Furthermore, large buttons required a significantly shorter task completion time than small buttons. There was no significant difference in the number of errors between the two sizes. A distance of at least 80 cm from the eye to the virtual object is most favorable for a good performance. There was a significant difference in the task completion times between 40 cm and 80 cm and between 40 cm and 120 cm. These results can aid the interface designs for AR applications and devices.

Meal-assistance robots (MARs) help feed meals to users with disabilities or who need help consuming their meals. Although such MARs have been introduced in various fields, guidelines for evaluating MARs are limited. This study aims to develop comprehensive guidelines to assess the user experience (UX) of MAR designs considering its social interaction characteristics between humans and robots. Participants from three groups (patients, doctors, and caregivers) with different perspectives on MARs were recruited and a focus group interview was conducted to collect their UXs with MARs. The three groups showed different UXs with MARs in user interface design, robot arm motion, and safety and mobility. In addition, based on the literature review, eight UX features (usability, emotion, value, naturalness, assistance, acceptance, personality, and culture) are proposed to evaluate MAR interfaces. The proposed comprehensive design guideline will be particularly useful in evaluating and designing the UX of MARs.

Virtual reality (VR) devices have recently become popular; however, research on input methods for VR devices is lacking. The main input methods of current commercial devices can be classified into two categories: manual selection using a controller and gaze selection. This study aims to derive the optimal input method and timing for VR devices by analyzing the performance of these input methods. A study is conducted in which participants wear a VR headset and select an activated input button from a 3 × 3 array on a VR device with two button sizes and two input methods. The manual selection method exhibits a shorter task completion time but a greater error number compared to the gaze selection method. For the gaze selection method, the task completion time and target search time were shortest when the gaze timing was 1 s. Further, the button size was determined to be statistically significant only when the manual selection method was used. The results of this study can be used as a reference in future VR user experience and product design.

Amid the increasing popularity of smartphones fitted with touch screens, many studies have been conducted on touch screen input methods. In contrast to standardized stylus pens, the size and anthropometric features of the fingers can be vastly different depending on the person. These features significantly impact the touch screen’s usability for an individual. In this paper, the relationship between the anthropometrical dimensions of the thumb (i.e., length, breadth) and touch task performance was analyzed. Based on the results, subjects with relatively longer fingers required more time on average to complete the task. However, no correlation was evident between the thumb length and number of errors, or among the thumb breadth, task completion time, and error frequency. The results of this study are expected to be useful in the development of a mobile interface that considers the specific features of the user’s thumb.

Many people have significant difficulties while using information technology (IT) devices. This study suggests a new concept of IT interaction disability (ITID) to understand the significant difficulties that users may encounter while using IT devices. The task, interface, and context (TIC) framework for classifying the types of ITID is also developed; this framework includes three components: tasks, user interface elements, and context factors. A case study in which visually impaired people used smartphones was conducted to illustrate the types of ITID and to show the applicability of the TIC framework. The result of this study can provide insights to researchers to improve the understanding of the significant difficulties of using IT devices and to analyse these difficulties systematically.

The human arm exhibits outstanding manipulability in executing various tasks by taking advantage of its intrinsic compliance, force sensation, and tactile contact clues. By examining human strategy in controlling arm impedance, we may be able to understand underlying human motor control and develop control methods for dexterous robotic manipulation. This paper presents a novel method for estimating multijoint stiffness by using electromyogram (EMG) and an artificial neural network model. The artificial network model developed in this paper relates EMG data and joint motion data to joint stiffness. With the proposed method, the multijoint stiffness of the arm was estimated without complex calculation or specialized apparatus. The feasibility of the proposed method was confirmed through experimental and simulation results.