EEG-based brain-computer interfaces exploiting steady-state somatosensory-evoked potentials: a literature review

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Brain-computer interfaces (BCIs) translate brain activity into commands for external devices.
• BCIs are categorized as 'active' (detecting spontaneous mental state changes) or 'reactive' (detecting brain responses to external stimuli).
• Reactive BCIs often use sustained, periodical stimuli to elicit detectable brain responses, such as steady-state evoked potentials.

Purpose of the Study:

• To survey the scientific literature on electroencephalography-based BCIs (EEG-BCIs) that utilize steady-state somatosensory-evoked potentials (SSSEPs).
• To describe SSSEP characteristics and calibration techniques for maximizing signal amplitude.
• To review signal processing and classification algorithms used in SSSEP-based BCIs and their performance.

Main Methods:

• Literature review of EEG-based BCIs employing SSSEPs.
• Analysis of SSSEP generation through periodic somatosensory stimulation (mechanical or electrical).
• Examination of signal processing and data classification techniques for command generation.

Main Results:

• SSSEPs are oscillatory, phase-locked EEG responses to somatosensory stimulation.
• SSSEP amplitude modulation by mental tasks (e.g., attention) enables command translation.
• SSSEP-based BCIs combine reactive BCI analysis with active BCI self-paced interaction.

Conclusions:

• SSSEP-based BCIs present a promising approach by integrating advantages of both active and reactive BCI paradigms.
• Further research into SSSEP characteristics, calibration, and advanced signal processing can enhance BCI performance.
• This review provides a comprehensive overview of the field, aiding future development and research in SSSEP-BCIs.