An ensemble deep-learning approach for single-trial EEG classification of vibration intensity

Neural correlates of thermal stimulation during active touch

Introduction

Thermal feedback technologies have been explored in human-computer interaction to provide secondary information and enhance the overall user experience. Unlike fast-response haptic modalities such as vibration and force feedback, the human brain's processes associated with thermal feedback are not fully understood.

Methods

In this study, we utilize electroencephalography (EEG) brain imaging to systematically examine the neural correlates associated with a wide range of thermal stimuli, including 9, 15, 32, and 42°C, during active touch at the fingertip. A custom experimental setup is developed to provide thermal stimulation at the desirable temperature levels. A total of 30 participants are recruited to experience the four levels of thermal stimulation by actively touching a thermal stimulation unit with the index finger while recording brain activities via EEG. Time-frequency analysis and power spectral density (PSD) of the EEG data are utilized to analyze the delta, theta, alpha, beta, and gamma frequency bands.

Results

The results show that the delta, theta, and alpha PSDs of 9 and 15°C stimuli are significantly higher than the PSDs of 32 and 42°C in the right frontal area during the early stage of the stimulation, from 282 ms up to 1,108 ms (One-way ANOVA test, Holm-Bonferroni correction, p < 0.05). No significant differences in PSDs are found between 9 and 15°C thermal stimuli or between 32 and 42°C thermal stimuli.

Discussion

The findings of this study inform the development of thermal feedback system in human-computer interaction.