Target selection is a fundamental interaction task in virtual reality (VR) systems, particularly for older adults who face unique challenges due to age-related declines in motor and cognitive abilities. While controller-based raycasting is widely used for its accuracy and efficiency, the design of selection feedback remains an open question, particularly in enhancing usability and accessibility for aging populations. In this study, we propose seven feedback techniques, including three uni-modal (visual, audio, haptic) and four multimodal (visual-audio, visual-haptic, audio-haptic, visual-audio-haptic) approaches. To evaluate these techniques, we conducted two user studies focusing on selection tasks in controlled and realistic scenarios. Our results indicate that visual-based feedback, particularly expansion techniques, significantly improves selection accuracy and user experience. Moreover, multimodal feedback does not always yield better performance; rather, a combination of visual and haptic feedback provides the most effective balance between usability and cognitive load. Based on our findings, we derive six design implications to guide the development of VR selection feedback tailored to older adults. This work contributes to the understanding of optimal selection feedback mechanisms, promoting more inclusive and accessible VR interactions for aging users.
Wei et al. (Thu,) studied this question.