Trial-based Classification of Haptic Tasks Based on EEG Data

Haneen Alsuradi, Mohamad Eid

Research output: Chapter in Book/Report/Conference proceedingConference contribution


With the increasing popularity of neural imaging techniques such as electroencephalography (EEG), developing quantitative measures to characterize haptic interactions is becoming a reality. Meanwhile, machine learning is a promising approach for trial-based EEG data analysis. This work presents a model that can distinguish between passive and active kinesthetic interactions based on a single trial EEG data. An interactive task that involves hitting a ball using a racket is developed under passive and active kinesthetic settings using a haptic device and a computer screen. Temporal and frequency domain features are extracted from the motor and somatosensory cortices, and a proposed 2-D CNN model is trained on data extracted from 19 participants. The model achieves a mean accuracy of 84.56%, 93.96%, and 95.89% across 5-fold validation when using one, four, or six electrodes, respectively. The model mechanism is assessed using an explainable machine learning algorithm, LIME, which shows that the model utilizes sensible features from a neuroscience perspective towards its prediction. This work paves the way for a better understanding of the neural mechanisms associated with kinesthetic haptic interaction, which proves helpful in many applications such as motor rehabilitation and brain-computer interactions, in addition to modeling the haptic quality of experience objectively.

Original languageEnglish (US)
Title of host publication2021 IEEE World Haptics Conference, WHC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665418713
StatePublished - Jul 6 2021
Event2021 IEEE World Haptics Conference, WHC 2021 - Virtual, Montreal, Canada
Duration: Jul 6 2021Jul 9 2021

Publication series

Name2021 IEEE World Haptics Conference, WHC 2021


Conference2021 IEEE World Haptics Conference, WHC 2021
CityVirtual, Montreal

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Control and Optimization
  • Sensory Systems


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