Falls represent a significant public health challenge for older adults, given their high incidence and potential for severe outcomes. Proactive identification of individuals at high fall risk through effective assessment is crucial for implementing targeted prevention strategies. Despite numerous fall risk assessment solutions available, a notable gap persists in objective and readily accessible assessment tools. Addressing this need, we proposed a novel application of video-based gait analysis for fall risk assessment utilizing a single red-green-blue (RGB) camera. Key spatiotemporal gait parameters were derived for risk modeling using two-dimensional human pose estimation and a predefined distance measure. This approach advances beyond existing frameworks that mainly rely on wearable sensors or depth cameras by providing a more practical and accessible alternative. To assess the efficacy of this approach, an experimental study was conducted with 99 community-dwelling older adults. The findings revealed significant differences in gait parameters between individuals categorized into high and low fall risk groups. Among commonly used classification algorithms, support vector machine (SVM) classifier yielded optimal performance, achieving an accuracy of 86.35 % alongside balanced sensitivity (87.55 %) and specificity (85.16 %). Model interpretability was further substantiated by consistent feature importance patterns observed across cross-validation folds, elucidated by SHapley Additive exPlanations (SHAP). Compared to current state-of-the-art fall risk assessment studies, our single RGB camera-based methodology demonstrates a more favorable balance of accuracy and practicality. This solution exhibits substantial promise for wider adoption in facilitating routine and more accessible fall risk screening for the older people in their daily environments.

In Fitts’ law research for pointing and selecting tasks, the multi-directional tapping task from ISO/TS 9241-411 has been widely used as a standard task. However, the ISO standard does not describe several task factors in sufficient detail, leading researchers to interpret and apply them independently in various ways. This study aims to investigate the effects of four task factors for multi-directional tapping task: error highlight, hover highlight, target shape, and number of targets. The experimental results indicated that all investigated task factors had significant effects on user performance and behavior, as reflected in both eye movement and mouse movement patterns. Our research findings can be helpful for researchers who want to evaluate the efficiency and effectiveness of interaction techniques and input devices for graphical user interfaces as a multi-directional tapping task protocol.

The multi-directional tapping task has long served as a foundational tool for evaluating pointing performance in human-computer interaction research. However, its transition from 2D interfaces to virtual reality (VR) raises challenges, especially in standardizing target depth. This study explores how target depth influences performance in VR, focusing on two common techniques: Raycasting and Virtual Hand. We conducted two controlled experiments (each with$\mathrm{n}=20$) to isolate depth effects. In Experiment 1, fixed target size led to visual angle (VA) shifts across depths, affecting performance. Both techniques performed best when VA was between$1-4^{\circ}$; Raycasting peaked at 2 m, Virtual Hand at$0.4-0.5 ~\mathrm{m}$. In Experiment 2, we controlled VA to isolate depth itself. Raycasting remained stable beyond 2 m but degraded at close range due to biomechanical limits. Virtual Hand remained sensitive to depth despite fixed VA, but differences were smaller, with throughput unaffected. These results suggest VA should be the primary parameter for standardizing the task in VR. Depth-specific evaluation remains necessary, except for Raycasting beyond 2 m. We provide depth-aware guidelines to improve standardization and comparability while aligning with ISO protocols.

Mid-air interaction in virtual reality (VR) offers a device-free and natural interface, but the absence of physical haptic feedback limits user experience. Pseudo-haptics, which leverage visual and auditory cues to induce the illusion of touch, provide a promising alternative. This study investigates the individual and combined effects of three pseudo-haptic feedback modalities: visual feedback of vibration (with varying frequency, amplitude, and duration), auditory feedback of vibration, and particle effects, on the perception and experience of mid-air button interactions in VR. An experiment with 36 participants subjectively evaluated 54 different virtual button conditions. The results show that visual vibration cues and particle effects significantly enhanced various aspects of the user experience, including haptic illusion, while auditory vibration feedback improved spatiotemporal perception and pragmatic quality. Among the modalities, particle effects had the strongest overall impact, and among the vibration parameters, duration was the most influential. Participant interviews revealed that excessive or incongruent multimodal feedback reduced the effectiveness and appeal of pseudo-haptic sensations. Furthermore, individual differences in preference suggest that personalized feedback settings could be advantageous. Based on the findings, we provide empirical guidelines for designing perceptually optimized pseudo-haptic feedback in VR button interfaces.

The aim of this study was to investigate the effect of different loading symbols and loading durations on online video viewers’ perception of waiting time. Sixty young adults participated in this study and their subjective ratings on waiting time perception for forty-eight different loading symbols (4 progress functions × 2 shapes × 2 embellishments × 3 durations) were obtained through a 7-point Likert scale. Each participant chose the best loading symbols in terms of waiting time perception at the end of the experiment. Results showed that duration and the progress function practically affect the viewers’ waiting time perception, and shape and embellishment do not. Loading symbols of power and inverse power progress functions are perceived as shorter than those of the repetitive and linear progress functions. It is recommended to show loading progress and use manipulated progress functions, and design factors such as shape and embellishment are considered to be less important for designing a better loading symbol. The findings of this study may serve as a useful input for video service providers and symbol designers in creating shortly perceived loading symbols.