This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening the understanding of human behaviors and intentions in various creative, cognitive, and physical activities that ultimately can facilitate the design and creation of innovative tools that enhance human life in multiple domains.

Virtual Reality (VR) may improve mental health through immersive self-expression and relaxing environments. However, co-design for these outcomes is challenging due to participants' limited experience with VR and unfamiliarity with self-expression and relaxation techniques. In this paper, we proposed VRelax, a virtual environment that will be designed to support stress relief through self-expression. We are using OpenBrush as a technology proof to provide participants with a self-expression VR experience before co-design sessions. Smartwatches and inertial sensors are used to collect heart rate and accelerometer data to evaluate participants' stress levels during VR experience. We hypothesize self-expressive VR experience will foster participants’ creativity in designing relaxation environments, and the multimodal data collected could identify which parts of the VR experience are more relaxing or stressful. Our findings will have implications to improve the co-design sessions by using VR as a technology proof and improve the design of VR experiences for relaxation.

This paper presents a novel approach to co-designing an immersive virtual reality (VR) experience where users can participate in a guessability process for a full gesture-based user interface for 3D content interactions using hand controllers. The proposed VR system includes animated visual prompts to allow users to create their own gestures for 13 different object interactions. A pilot study with two participants demonstrated that the visual prompts helped users understand expected interactions and enhanced their creativity in gesture design while maintaining an enjoyable user experience. Hand motion data and user feedback were collected and will be analyzed to provide quantitative insights into gesture efficiency and economy. This paper contributes to developing an intuitive and interactive gesture-based interface for VR and sets the foundation for future studies with more participants to gather additional gesture design ideas.