Archive/Artificial Intelligence-Based Evaluation of Brain–Tactile Interaction Using Electroencephalographic Signals and a Smart Haptic Glove
Artificial Intelligence-Based Evaluation of Brain–Tactile Interaction Using Electroencephalographic Signals and a Smart Haptic Glove
Kasidit Kokkhunthod, Talit Jumphoo, Wongsathon Pathonsuwan et al.
14 de julho de 2026
en

Abstract

Wearable vibrotactile devices are increasingly used in virtual reality, teleoperation and neurorehabilitation, but objective EEG evaluation of glove-mediated touch remains limited. We compared EEG recorded during natural object interaction with EEG recorded when tactile feedback was reproduced through a vibrotactile smart glove. Data were collected with an eight-channel wireless headset while participants interacted with three object types (bottle, cube, and sphere) in natural-touch and glove-mediated conditions. An exploratory model trained on natural-touch data and tested on glove-mediated trials yielded rounded cross-condition accuracies of 83%, 78%, and 68% for bottle vs. rest, cube vs. rest, and sphere vs. rest, respectively. These findings suggest that some object-related EEG patterns may carry across conditions, but they should not be interpreted as evidence of physiological equivalence. Supplementary analyses using repeated-run evaluation, band-power and ERD/ERS summaries, temporal-window inspection, and channel ablation were included as cautious interpretability checks. The results underscore the need for larger subject-independent studies, stronger artifact-control pipelines, formal statistical testing, and richer haptic conditions before asserting equivalence to natural touch.

IPC Classification

G06H04B60H01

Keywords

artificialintelligence-basedevaluationbraintactileinteractionelectroencephalographicsignalssmarthapticglovewearablevibrotactiledevicesincreasinglyusedvirtualrealityteleoperationneurorehabilitationobjectiveglove-mediatedtouchremains
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