In-Ear Electrode EEG for Practical SSVEP BCI

Mouli, Surej; Palaniappan, Ramaswamy; Molefi, Emmanuel; McLoughlin, Ian

doi:10.3390/technologies8040063

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…The personalization process is lengthy, costly, and strenuous. Using generic consumer earpieces with different electrodes attached is an easier process for manufacturing ear-EEG. − TipTrodes, commonly used as generic conductive earpieces, are disposable gold foil-covered polyurethane foam earpieces, which are readily available and used in in-ear research recordings. , They come in two cylinder sizes, 10 and 13 mm in diameter, and consist of a tubular insert to allow soundwaves to pass. The idea of a generic and off-the-shelf earpiece for ear-EEG was first introduced by Kidmose et al in hopes of establishing a practical prototype.…”

Section: In-ear Eeg (Ear-eeg)mentioning

confidence: 99%

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Petrossian

Kateb

Miquet-Westphal

et al. 2023

ACS Appl. Bio Mater.

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Electroencephalogram (EEG) records the electrical activity of neurons in the cerebral cortex and is used extensively to diagnose, treat, and monitor psychiatric and neurological conditions. Reliable contact between the skin and the electrodes is essential for achieving consistency and for obtaining electroencephalographic information. There has been an increasing demand for effective equipment and electrodes to overcome the time-consuming and cumbersome application of traditional systems. Recently, ear-centered EEG has met with growing interest since it can provide good signal quality due to the proximity of the ear to the brain. In addition, it can facilitate mobile and unobtrusive usage due to its smaller size and ease of use, since it can be used without interfering with the patient’s daily activities. The purpose of this mini-review is to first introduce the broad range of electrodes used in conventional (scalp) EEG and subsequently discuss the state-of-the-art literature about around- and in-the-ear EEG.

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Section: In-ear Eeg (Ear-eeg)mentioning

confidence: 99%

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Petrossian

Kateb

Miquet-Westphal

et al. 2023

ACS Appl. Bio Mater.

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“…Some other studies designed BCI based on SSVEPs measured from hairless areas. However, without redesigning the stimulation paradigm to better adapt to the new area, the SNR of the response in the hairless area is relatively low (Wang et al 2016, Ahn et al 2018, Floriano et al 2018, Kappel and Kidmose 2018, Chan et al 2018, Kwak and Lee 2020, Mouli et al 2020, Zhu et al 2021. Therefore, a better stimulation paradigm needed to be developed to achieve high ITR in the hairless area, such as by introducing spatial coding to SSVEP-BCI.…”

Section: Background and Purposementioning

confidence: 99%

Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear

Liang¹,

Bin²,

Chen³

et al. 2021

J. Neural Eng.

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Objective. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) has the characteristics of fast communication speed, high stability, and wide applicability, thus it has been widely studied. With the rapid development in paradigm, algorithm, and system design, SSVEP-BCI is gradually applied in clinical and real-life scenarios. In order to improve the ease of use of the SSVEP-BCI system, many studies have been focusing on developing it on the hairless area, but due to the lack of redesigning the stimulation paradigm to better adapt to the new area, the EEG response in the hairless area is worse than occipital region. Approach. This study first proposed a phase difference estimation method based on stimulating the left and right visual field separately, then developed and optimized a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear. Main results. In the 12-target online experiment, after a short model estimation training, all sixteen subjects used their best stimulus condition. The paradigm designed in this study can increase the proportion of applicable subjects for the behind-ear SSVEP-BCI system from 58.3% to 75% and increase the accuracy from 74.6±20.0% (the existing best SSVEP stimulus with hairless region behind the ear) to 84.2±14.7%, and the ITR from 14.2±6.4bits/min to 17.8±5.7bits/min. Significance. These results demonstrated that the proposed paradigm can effectively improve the BCI performance using the signal from the hairless region behind the ear, compared with the standard SSVEP stimulation paradigm.

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“…The EEG headset converts data into packets and transmits them to a Personal Computer (PC) over a wireless medium (Bluetooth). The Brain-Computer Interface (BCI) system allows communication between the headset and the PC [7].…”

Section: Introductionmentioning

confidence: 99%

Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

Riaz¹,

Ali²,

Anwar³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Electroencephalogram (EEG) is a method of capturing the electrophysiological signal of the brain. An EEG headset is a wearable device that records electrophysiological data from the brain. This paper presents the design and fabrication of a customized low-cost Electroencephalogram (EEG) headset based on the open-source OpenBCI Ultracortex Mark IV system. The electrode placement locations are modified under a 10-20 standard system. The fabricated headset is then compared to commercially available headsets based on the following parameters: affordability, accessibility, noise, signal quality, and cost. First, the data is recorded from 20 subjects who used the EEG Headset, and signals were recorded. Secondly, the participants marked the accuracy, set up time, participant comfort, and participant perceived ease of set-up on a scale of 1 to 7 (7 being excellent). Thirdly, the self-designed EEG headband is used by 5 participants for slide changing. The raw EEG signal is decomposed into a series of band signals using discrete wavelet transform (DWT). Lastly, these findings have been compared to previously reported studies. We concluded that when used for slide-changing control, our self-designed EEG headband had an accuracy of 82.0 percent. We also concluded from the results that our headset performed well on the cost-effectiveness scale, had a reduced setup time of 2 ± 0.5 min (the shortest among all being compared), and demonstrated greater ease of use.

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In-Ear Electrode EEG for Practical SSVEP BCI

Cited by 8 publications

References 22 publications

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Advances in Electrode Materials for Scalp, Forehead, and Ear EEG: A Mini-Review

Optimizing a left and right visual field biphasic stimulation paradigm for SSVEP-based BCIs with hairless region behind the ear

Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

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