Published: 6 March 2024| Version 2 | DOI: 10.17632/z6dfjh596r.2


WheelSimPhysio-2023 dataset with implicit, explicit and performance data. The Implicit is the physiological responses throughout all the states of the experiment. Explicit measures are questionnaires and rating scales collected via the post-experience feedback phase. The performance metrics included joystick events, time to complete and the number of collisions that were captured inside the application. These metrics are widely used in the Quality of Experience evaluations.


Steps to reproduce

- Dataset overview: WheelSimPhysio-2023 dataset were collected from two types of experiments with the same wheelchair training simulator presented on https://doi.org/10.1145/3524273.3528175 : o Experiment 1: the simulator was presented on a PC with a conventional monitor. It was collected data from non-wheelchair users (Nmonitor =24 participants). We collected a baseline data (5 minutes resting phase), test data (simulation activity) and post-experience assessment (participants answered questionnaires on a paper-based version). o Experiment 2: the simulator was configured as fully immersive by using VR HMD, with the same PC and same data collection protocol. It was collected data from 34 participants, split into two groups (Nhigh-jerk=18 and Nlow-jerk=16). The first VR group experienced the virtual wheelchair with a high jolt (jerk) sensation when wheelchair start and stopped and the second group had the settings with less jolt sensation. - Hardware/Software specifications: oWheelchair Simulator: the application was developed using the Unity game engine in a PC machine that operates with monitor or VR HMD. o Physiological data: the physiological response was collected by using the Empatica E4 wristband. It has four sensors to determine the blood volume pressure (BVP) at a sample rate of 64 Hz, interbeat interval (IBI), Heart Rate (HR) in a sample rate of 1 Hz, electrodermal activity (GSR/EDA) at a sample rate of 4 Hz, XYZ raw acceleration at a sample rate of 32 Hz and the skin temperature at a sample rate of 4 Hz. The EEG data was collected using Mindwave Mobile from Neurosky, is one channel EEG device, the electrodes are dry type, its bandwidth is between 3 to 100 Hertz (Hz), with 12 bits of resolution, sample rate is 512 Hz and the transmission is made via Bluetooth. Eye-gaze and head pose were collected using a HP w200 camera with OpenFace framework. - Data processing code: the scripts for basic processing steps can be found at https://github.com/deborasal/WheelSimPhysio-2023.git


Athlone Institute of Technology, Universidade Federal de Uberlandia


Computer-Based Training, Human-Computer Interaction, Wheelchair Design, Immersive Virtual Reality, Physiological Response