Wearable in‐the‐ear EEG system for SSVEP‐based brain–computer interface. Issue 7 (1st April 2018)

• Record Type: Journal Article
• Authors: Ahn, J.W.; Ku, Y.; Kim, D.Y.; Sohn, J.; Kim, J.‐H.; Kim, H.C.
• Is Part Of: Electronics letters. Volume 54:Issue 7(2018)
• Page Start: 413
• Page End: 414
• Publication Date: 2018-04-01
• Subjects: electroencephalography -- ear -- body sensor networks -- brain‐computer interfaces -- visual evoked potentials -- medical signal processing -- signal denoising -- biomedical electrodes -- patient monitoring; wearable in‐the‐ear EEG system -- SSVEP‐based brain‐computer interface -- steady‐state visual evoked potential -- electroencephalogram‐based brain‐computer interfaces -- high information transfer rate -- short training time -- electrodes -- noise level -- offline BCI experiment -- visual targets -- unobtrusive monitoring -- BCI applications; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2017.3970
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : Steady‐state visual evoked potential (SSVEP) has been widely used in electroencephalogram (EEG)‐based brain–computer interfaces (BCIs) due to its high information transfer rate (ITR) and short training time. Current methods usually measure SSVEP from electrodes on the scalp, which is an uncomfortable and time‐consuming method. Furthermore, most research relies on expensive and non‐portable EEG devices. To utilise BCIs in daily life, however, these are critical issues to address. Hence, a wearable EEG device for in‐ear SSVEP detection is proposed. The system is 40 × 21 × 10.5 mm 3 and weighs 14.2 g, thus being light weight and wearable. Moreover, the system has a noise level of 0.11 µVrms, which is comparable with commercial EEG systems. Six subjects participated in an offline BCI experiment that consisted of six visual targets using the developed in‐the‐ear EEG system. The results showed a highest ITR of 11.03 ± 4.18 bits/min with an accuracy of 79.9 ± 13.1%, and the experiments demonstrated that the system can be utilised for unobtrusive monitoring of SSVEP in BCI applications.