Data in Brief (Jun 2024)
WheelSimPhysio-2023 dataset: Physiological and questionnaire-based dataset of immersive multisensory wheelchair simulator from 58 participants
Abstract
This data paper presents a unique multimodal dataset collected from a comprehensive experiment using a wheelchair training simulator. The dataset consists of quantitative and qualitative data that represents the user's experience and performance. Participants engaged in a series of navigational tasks in a simulated environment under two distinct system configuration conditions: a. a conventional monitor display and b. a virtual reality (VR) headset. The monitor group has a total of 24 participants data while using the simulator with a standard display and then other two groups of 18 and 16 respectively using the VR headset with a different wheelchair's speed profile. It was collected data from total of 58 participants.The dataset includes physiological data - Heart Rate Variability (HRV), Electrodermal Activity (EDA), Acceleration (ACC), Skin Temperature, Heart Rate (HR), and Blood Volume Pulse (BVP) - collected during both experiments. Additionally, for the standard display condition, more detailed data comprising Electroencephalography (EEG) and eye-tracking metrics were recorded to provide insights into cognitive load and visual attention patterns.System metrics captured from the simulator provide an objective performance report, including task completion times, error rates (collision of the virtual wheelchair), number of joystick commands. Also, the navigation efficiency data is complemented by post-experiment questionnaires, which gathered subjective responses on user experience, perceived difficulty, the user immersive levels, arousal, and simulator sickness symptoms.This dataset is valuable for researchers and practitioners in the fields of assistive technology, human-computer interaction, and rehabilitation. It offers metrics to a comprehensive view of how different display technologies influence the user experience in wheelchair simulation training. The data allows for in-depth analysis of physiological responses, cognitive engagement, and subjective perceptions, providing a foundation for future research on effective wheelchair training methodologies and the potential benefits of VR in rehabilitation settings.
