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On the Feasibility of Using an Ear-EEG to Develop an Endogenous Brain-Computer Interface.
Soo-In Choi1, Chang-Hee Han2, Ga-Young Choi3
1Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea. sooin1118@naver.com.
Sensors (Basel, Switzerland)
|August 31, 2018
Summary
This study shows that ear electroencephalography (EEG) can reliably detect brain activity from cognitive tasks, enabling new endogenous brain-computer interface (BCI) systems without external stimuli.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Human-Computer Interaction
Background:
- Existing brain-computer interface (BCI) research using ear electroencephalography (ear-EEG) primarily relies on exogenous paradigms triggered by external stimuli.
- There is a need to explore endogenous paradigms, which utilize self-modulated brain activity, for more versatile BCI applications.
Purpose of the Study:
- To investigate the feasibility of using ear-EEG for developing an endogenous BCI system.
- To assess the reliability of ear-EEG signals compared to traditional scalp-EEG during cognitive tasks.
Main Methods:
- Conducted preliminary and main experiments measuring EEG from both scalp and ear locations.
- Subjects performed tasks involving eyes-open/closed states and cognitive challenges like mental arithmetic (MA) and light cognitive (LC) tasks.
- Analyzed brain activity across four regions of interest (ROIs): frontal, central, occipital, and ear area.
Main Results:
- Preliminary experiment: Alpha activity increase in the ear area during eyes-closed tasks was comparable to other ROIs.
- Main experiment: Similar event-related (de)synchronization (ERD/ERS) patterns were observed across all ROIs during MA and LC tasks.
- Classification accuracy for distinguishing between MA and LC tasks exceeded 70% in all ROIs, including the ear area.
Conclusions:
- Ear-EEG is a reliable measure for detecting brain activity modulated by cognitive tasks.
- Ear-EEG can be effectively utilized for developing endogenous BCI systems, expanding its practical applications beyond exogenous paradigms.
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