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Quantifying Different Tactile Sensations Evoked by Cutaneous Electrical Stimulation Using Electroencephalography

Dingguo Zhang1, Fei Xu1, Heng Xu1

  • 11 State Key Laboratory of Mechanical Systems and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, #800 Dongchuan Road, Minhang District, Shanghai 200240, P. R. China.

International Journal of Neural Systems
|January 15, 2016
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This study introduces electroencephalography (EEG) to objectively quantify tactile sensations like vibration and pressure. EEG features successfully distinguished sensation types and grades, offering potential for medical and engineering applications.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Sensory Science

Background:

  • Traditional tactile sensation analysis relies on subjective psychophysical tests and questionnaires.
  • Objective quantification of tactile sensation remains a challenge for medical diagnosis and engineering applications.

Purpose of the Study:

  • To explore the potential of electroencephalography (EEG) for objective quantification of tactile sensations.
  • To differentiate between vibration and pressure sensations and their respective grades using EEG.
  • To investigate the utility of event-related potentials (ERPs) and event-related synchronization/desynchronization (ERS/ERD) as objective measures.

Main Methods:

  • Cutaneous electrical stimulation was used to induce vibration and pressure sensations of varying intensities in eight subjects.
Keywords:
Tactile sensationelectroencephalographyelectrotactile stimulationevent-related potentialevent-related synchronization/desynchronization

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  • EEG data was recorded and analyzed for event-related potentials (ERPs) and mu rhythm (8–13 Hz) ERS/ERD.
  • Statistical analyses were performed on individual and grand-averaged data to assess discrimination capabilities.

    • Main Results:

    • Specific ERP components (N2 and P3) significantly discriminated between vibration and pressure sensations.
    • Grand-averaged ERPs distinguished between three sensation grades, though individual results were not significant.
    • ERS/ERD features of the mu rhythm also showed potential in discriminating sensation types and grades, with significant results in grand-averaged data and some individuals.

    Conclusions:

    • EEG-based features, specifically ERPs and ERS/ERD, demonstrate potential for objectively quantifying tactile sensations.
    • This approach may offer a valuable tool for medical diagnostics and engineering applications requiring precise tactile assessment.