A Psychophysical Dataset for Vibrotactile Augmented Perception
Year: 2026
Type: data-paper
Abstract: Tactile perception modeling has been important research topic for years. However, due to individual differences and complexity of human cognition, the tactile perception modeling is challenging. One of the main challenges in this field is the lack of a rich dataset with sufficient inter-subject, inter-session, and intra-session diversities. Here, for the first time, we present a dataset of human position and intensity perception for 51 different vibration patterns. The dataset includes the experimental results for 40 individuals (20 female and 20 male) in two different sessions. The experimental results include the perceived intensity and position of each vibration pattern as well as selection time and confidence level. After each session the participants were also asked to fill a questionnaire file. We also collected the anthropometric and demographic data, and the participants underwent Bioelectrical Impedance Analysis (BIA) to measure body composition indicators. The detailed results for each participant is located in the dataset. This dataset can be used to develop tactile perception models, study individuals' perception differences, and design tactile sensory feedback.
Source: Scientific Data
Institution: University of Tehran
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,490
Award: G970602994
OpenAlex ID: W7130467708
