Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (18)

Search Parameters:
Keywords = dry electroencephalogram (EEG) electrodes

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
13 pages, 5782 KiB  
Article
Neonatal Electroencephalogram Recording with a Dry Electrode Cap: A Feasibility Study
by Amirreza Asayesh, Indhika Fauzhan Warsito, Jens Haueisen, Patrique Fiedler and Sampsa Vanhatalo
Sensors 2025, 25(3), 966; https://doi.org/10.3390/s25030966 - 5 Feb 2025
Viewed by 1800
Abstract
This study investigates the feasibility of a dry electrode cap design for neonatal electroencephalogram (EEG) recordings. Recordings on a phantom and a real infant are compared between a novel dry electrode cap and a clinically used gel-based electrode cap. The phantom recordings included [...] Read more.
This study investigates the feasibility of a dry electrode cap design for neonatal electroencephalogram (EEG) recordings. Recordings on a phantom and a real infant are compared between a novel dry electrode cap and a clinically used gel-based electrode cap. The phantom recordings included measuring both the electrode contact force and the signal quality during still and respiration-like head motion. The real infant recordings were assessed for the EEG signals’ spectral characteristics, including powerline interference. Compared to gel-based caps, the dry caps showed a largely comparable skin force, an expectedly greater sensitivity to motion-induced artifacts, and a slightly lower powerline interference. Recordings on the real infant showed no significant skin marks after using the dry electrode, and the spectral compositions were comparable between dry- and gel-based electrode caps. These findings suggest that neonatal EEG recordings with a dry electrode cap are technically feasible, but movement-related artifacts, such as respiration in a supine lying infant, may challenge long-term recordings of spontaneous EEG activity. Yet, the ease of use of dry electrode caps calls for future studies to define the optimal use case in neonatal recordings. Full article
(This article belongs to the Section Wearables)
Show Figures

Figure 1

14 pages, 3684 KiB  
Article
The Posterior Dominant Rhythm Remains Within Normal Limits in the Microgravity Environment
by Vasileios Kokkinos, Andreas M. Koupparis, Tomer Fekete, Eran Privman, Ofer Avin, Ophir Almagor, Oren Shriki and Amir Hadanny
Brain Sci. 2024, 14(12), 1194; https://doi.org/10.3390/brainsci14121194 - 27 Nov 2024
Viewed by 2113
Abstract
Background: Electroencephalogram (EEG) biomarkers with adequate sensitivity and specificity to reflect the brain’s health status can become indispensable for health monitoring during prolonged missions in space. The objective of our study was to assess whether the basic features of the posterior dominant rhythm [...] Read more.
Background: Electroencephalogram (EEG) biomarkers with adequate sensitivity and specificity to reflect the brain’s health status can become indispensable for health monitoring during prolonged missions in space. The objective of our study was to assess whether the basic features of the posterior dominant rhythm (PDR) change under microgravity conditions compared to earth-based scalp EEG recordings. Methods: Three crew members during the 16-day AXIOM-1 mission to the International Space Station (ISS), underwent scalp EEG recordings before, during, and after the mission by means of a dry-electrode self-donning headgear designed to support long-term EEG recordings in space. Resting-state recordings were performed with eyes open and closed during relaxed wakefulness. The electrodes representative of EEG activity in each occipital lobe were used, and consecutive PDR oscillations were identified during periods of eye closure. In turn, cursor-based markers were placed at the negative peak of each sinusoidal wave of the PDR. Waveform averaging and time-frequency analysis were performed for all PDR samples for the respective pre-mission, mission, and post-mission EEGs. Results: No significant differences were found in the mean frequency of the PDR in any of the crew subjects between their EEG on the ISS and their pre- or post-mission EEG on ground level. The PDR oscillations varied over a ±1Hz standard deviation range. Similarly, no significant differences were found in PDR’s power spectral density. Conclusions: Our study shows that the spectral features of the PDR remain within normal limits in a short exposure to the microgravity environment, with its frequency manifesting within an acceptable ±1 Hz variation from the pre-mission mean. Further investigations for EEG features and markers reflecting the human brain neurophysiology during space missions are required. Full article
Show Figures

Figure 1

16 pages, 6720 KiB  
Article
Stretchable Ag/AgCl Nanowire Dry Electrodes for High-Quality Multimodal Bioelectronic Sensing
by Tianyu Wang, Shanshan Yao, Li-Hua Shao and Yong Zhu
Sensors 2024, 24(20), 6670; https://doi.org/10.3390/s24206670 - 16 Oct 2024
Cited by 3 | Viewed by 2403
Abstract
Bioelectrical signal measurements play a crucial role in clinical diagnosis and continuous health monitoring. Conventional wet electrodes, however, present limitations as they are conductive gel for skin irritation and/or have inflexibility. Here, we developed a cost-effective and user-friendly stretchable dry electrode constructed with [...] Read more.
Bioelectrical signal measurements play a crucial role in clinical diagnosis and continuous health monitoring. Conventional wet electrodes, however, present limitations as they are conductive gel for skin irritation and/or have inflexibility. Here, we developed a cost-effective and user-friendly stretchable dry electrode constructed with a flexible network of Ag/AgCl nanowires embedded in polydimethylsiloxane (PDMS). We compared the performance of the stretched Ag/AgCl nanowire electrode with commonly used commercial wet electrodes to measure electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG) signals. All the signal-to-noise ratios (SNRs) of the as-fabricated or stretched (50% tensile strain) Ag/AgCl nanowire electrodes are higher than that measured by commercial wet electrodes as well as other dry electrodes. The evaluation of ECG signal quality through waveform segmentation, the signal quality index (SQI), and heart rate variability (HRV) reveal that both the as-fabricated and stretched Ag/AgCl nanowire electrode produce high-quality signals similar to those obtained from commercial wet electrodes. The stretchable electrode exhibits high sensitivity and dependability in measuring EMG and EEG data, successfully capturing EMG signals associated with muscle activity and clearly recording α-waves in EEG signals during eye closure. Our stretchable dry electrode shows enhanced comfort, high sensitivity, and convenience for curved surface biosignal monitoring in clinical contexts. Full article
(This article belongs to the Section Biomedical Sensors)
Show Figures

Figure 1

22 pages, 4691 KiB  
Article
Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
by Brian Premchand, Liyuan Liang, Kok Soon Phua, Zhuo Zhang, Chuanchu Wang, Ling Guo, Jennifer Ang, Juliana Koh, Xueyi Yong and Kai Keng Ang
NeuroSci 2024, 5(4), 407-428; https://doi.org/10.3390/neurosci5040031 - 8 Oct 2024
Cited by 3 | Viewed by 6461
Abstract
Detecting stress is important for improving human health and potential, because moderate levels of stress may motivate people towards better performance at cognitive tasks, while chronic stress exposure causes impaired performance and health risks. We propose a Brain–Computer Interface (BCI) system to detect [...] Read more.
Detecting stress is important for improving human health and potential, because moderate levels of stress may motivate people towards better performance at cognitive tasks, while chronic stress exposure causes impaired performance and health risks. We propose a Brain–Computer Interface (BCI) system to detect stress in the context of high-pressure work environments. The BCI system includes an electroencephalogram (EEG) headband with dry electrodes and an electrocardiogram (ECG) chest belt. We collected EEG and ECG data from 40 participants during two stressful cognitive tasks: the Cognitive Vigilance Task (CVT), and the Multi-Modal Integration Task (MMIT) we designed. We also recorded self-reported stress levels using the Dundee Stress State Questionnaire (DSSQ). The DSSQ results indicated that performing the MMIT led to significant increases in stress, while performing the CVT did not. Subsequently, we trained two different models to classify stress from non-stress states, one using EEG features, and the other using heart rate variability (HRV) features extracted from the ECG. Our EEG-based model achieved an overall accuracy of 81.0% for MMIT and 77.2% for CVT. However, our HRV-based model only achieved 62.1% accuracy for CVT and 56.0% for MMIT. We conclude that EEG is an effective predictor of stress in the context of stressful cognitive tasks. Our proposed BCI system shows promise in evaluating mental stress in high-pressure work environments, particularly when utilizing an EEG-based BCI. Full article
Show Figures

Figure 1

24 pages, 10077 KiB  
Article
Emotion Recognition Using EEG Signals through the Design of a Dry Electrode Based on the Combination of Type 2 Fuzzy Sets and Deep Convolutional Graph Networks
by Shokoufeh Mounesi Rad and Sebelan Danishvar
Biomimetics 2024, 9(9), 562; https://doi.org/10.3390/biomimetics9090562 - 18 Sep 2024
Cited by 3 | Viewed by 2432
Abstract
Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). [...] Read more.
Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). To achieve this objective, a dry EEG electrode is created using the silver-copper sintering technique, which is assessed through Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Analysis (EDXA) evaluations. Subsequently, a database is generated utilizing the designated electrode, which is based on the musical stimulus. The collected data are fed into an improved deep network for automatic feature selection/extraction and classification. The deep network architecture is structured by combining type 2 fuzzy sets (FT2) and deep convolutional graph networks. The fabricated electrode demonstrated superior performance, efficiency, and affordability compared to other electrodes (both wet and dry) in this study. Furthermore, the dry EEG electrode was examined in noisy environments and demonstrated robust resistance across a diverse range of Signal-To-Noise ratios (SNRs). Furthermore, the proposed model achieved a classification accuracy of 99% for distinguishing between positive and negative emotions, an improvement of approximately 2% over previous studies. The manufactured dry EEG electrode is very economical and cost-effective in terms of manufacturing costs when compared to recent studies. The proposed deep network, combined with the fabricated dry EEG electrode, can be used in real-time applications for long-term recordings that do not require gel. Full article
Show Figures

Figure 1

20 pages, 7142 KiB  
Article
A Film Electrode upon Nanoarchitectonics of Bacterial Cellulose and Conductive Fabric for Forehead Electroencephalogram Measurement
by Kunpeng Gao, Nailong Wu, Bowen Ji and Jingquan Liu
Sensors 2023, 23(18), 7887; https://doi.org/10.3390/s23187887 - 14 Sep 2023
Cited by 8 | Viewed by 1999
Abstract
In this paper, we present a soft and moisturizing film electrode based on bacterial cellulose and Ag/AgCl conductive cloth as a potential replacement for gel electrode patches in electroencephalogram (EEG) recording. The electrode materials are entirely flexible, and the bacterial cellulose membrane facilitates [...] Read more.
In this paper, we present a soft and moisturizing film electrode based on bacterial cellulose and Ag/AgCl conductive cloth as a potential replacement for gel electrode patches in electroencephalogram (EEG) recording. The electrode materials are entirely flexible, and the bacterial cellulose membrane facilitates convenient adherence to the skin. EEG signals are transmitted from the skin to the bacterial cellulose first and then transferred to the Ag/AgCl conductive cloth connected to the amplifier. The water in the bacterial cellulose moisturizes the skin continuously, reducing the contact impedance to less than 10 kΩ, which is lower than commercial gel electrode patches. The contact impedance and equivalent circuits indicate that the bacterial cellulose electrode effectively reduces skin impedance. Moreover, the bacterial cellulose electrode exhibits lower noise than the gel electrode patch. The bacterial cellulose electrode has demonstrated success in collecting α rhythms. When recording EEG signals, the bacterial cellulose electrode and gel electrode have an average coherence of 0.86, indicating that they have similar performance across different EEG bands. Compared with current mainstream conductive rubber dry electrodes, gel electrodes, and conductive cloth electrodes, the bacterial cellulose electrode has obvious advantages in terms of contact impedance. The bacterial cellulose electrode does not cause skin discomfort after long-term recording, making it more suitable for applications with strict requirements for skin affinity than gel electrode patches. Full article
(This article belongs to the Special Issue EEG Sensors for Biomedical Applications)
Show Figures

Figure 1

22 pages, 9635 KiB  
Article
Hook Fabric Electroencephalography Electrode for Brain Activity Measurement without Shaving the Head
by Granch Berhe Tseghai, Benny Malengier, Kinde Anlay Fante and Lieva Van Langenhove
Polymers 2023, 15(18), 3673; https://doi.org/10.3390/polym15183673 - 6 Sep 2023
Cited by 4 | Viewed by 2591
Abstract
In this research, novel electroencephalogram (EEG) electrodes were developed to detect high-quality EEG signals without the requirement of conductive gels, skin treatments, or head shaving. These electrodes were created using electrically conductive hook fabric with a resistance of 1 Ω/sq. The pointed hooks [...] Read more.
In this research, novel electroencephalogram (EEG) electrodes were developed to detect high-quality EEG signals without the requirement of conductive gels, skin treatments, or head shaving. These electrodes were created using electrically conductive hook fabric with a resistance of 1 Ω/sq. The pointed hooks of the conductive fabric establish direct contact with the skin and can penetrate through hair. To ensure excellent contact between the hook fabric electrode and the scalp, a knitted-net EEG bridge cap with a bridging effect was employed. The results showed that the hook fabric electrode exhibited lower skin-to-electrode impedance compared to the dry Ag/AgCl comb electrode. Additionally, it collected high-quality signals on par with the standard wet gold cups and commercial dry Ag/AgCl comb electrodes. Moreover, the hook fabric electrode displayed a higher signal-to-noise ratio (33.6 dB) with a 4.2% advantage over the standard wet gold cup electrode. This innovative electrode design eliminates the need for conductive gel and head shaving, offering enhanced flexibility and lightweight characteristics, making it ideal for integration into textile structures and facilitating convenient long-term monitoring. Full article
(This article belongs to the Special Issue Polymeric Materials in Sensor Applications)
Show Figures

Graphical abstract

19 pages, 12624 KiB  
Article
Characterizing the Impedance Properties of Dry E-Textile Electrodes Based on Contact Force and Perspiration
by Vignesh Ravichandran, Izabela Ciesielska-Wrobel, Md Abdullah al Rumon, Dhaval Solanki and Kunal Mankodiya
Biosensors 2023, 13(7), 728; https://doi.org/10.3390/bios13070728 - 13 Jul 2023
Cited by 13 | Viewed by 4626
Abstract
Biopotential electrodes play an integral role within smart wearables and clothing in capturing vital signals like electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). This study focuses on dry e-textile electrodes (E1–E6) and a laser-cut knit electrode (E7), to assess their impedance characteristics under [...] Read more.
Biopotential electrodes play an integral role within smart wearables and clothing in capturing vital signals like electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). This study focuses on dry e-textile electrodes (E1–E6) and a laser-cut knit electrode (E7), to assess their impedance characteristics under varying contact forces and moisture conditions. Synthetic perspiration was applied using a moisture management tester and impedance was measured before and after exposure, followed by a 24 h controlled drying period. Concurrently, the signal-to-noise ratio (SNR) of the dry electrode was evaluated during ECG data collection on a healthy participant. Our findings revealed that, prior to moisture exposure, the impedance of electrodes E7, E5, and E2 was below 200 ohm, dropping to below 120 ohm post-exposure. Embroidered electrodes E6 and E4 exhibited an over 25% decrease in mean impedance after moisture exposure, indicating the impact of stitch design and moisture on impedance. Following the controlled drying, certain electrodes (E1, E2, E3, and E4) experienced an over 30% increase in mean impedance. Overall, knit electrode E7, and embroidered electrodes E2 and E6, demonstrated superior performance in terms of impedance, moisture retention, and ECG signal quality, revealing promising avenues for future biopotential electrode designs. Full article
(This article belongs to the Special Issue Devices and Wearable Devices toward Innovative Applications)
Show Figures

Figure 1

15 pages, 6331 KiB  
Article
Development of Low-Contact-Impedance Dry Electrodes for Electroencephalogram Signal Acquisition
by Ramona B. Damalerio, Ruiqi Lim, Yuan Gao, Tan-Tan Zhang and Ming-Yuan Cheng
Sensors 2023, 23(9), 4453; https://doi.org/10.3390/s23094453 - 2 May 2023
Cited by 9 | Viewed by 6761
Abstract
Dry electroencephalogram (EEG) systems have a short set-up time and require limited skin preparation. However, they tend to require strong electrode-to-skin contact. In this study, dry EEG electrodes with low contact impedance (<150 kΩ) were fabricated by partially embedding a polyimide flexible printed [...] Read more.
Dry electroencephalogram (EEG) systems have a short set-up time and require limited skin preparation. However, they tend to require strong electrode-to-skin contact. In this study, dry EEG electrodes with low contact impedance (<150 kΩ) were fabricated by partially embedding a polyimide flexible printed circuit board (FPCB) in polydimethylsiloxane and then casting them in a sensor mold with six symmetrical legs or bumps. Silver–silver chloride paste was used at the exposed tip of each leg or bump that must touch the skin. The use of an FPCB enabled the fabricated electrodes to maintain steady impedance. Two types of dry electrodes were fabricated: flat-disk electrodes for skin with limited hair and multilegged electrodes for common use and for areas with thick hair. Impedance testing was conducted with and without a custom head cap according to the standard 10–20 electrode arrangement. The experimental results indicated that the fabricated electrodes exhibited impedance values between 65 and 120 kΩ. The brain wave patterns acquired with these electrodes were comparable to those acquired using conventional wet electrodes. The fabricated EEG electrodes passed the primary skin irritation tests based on the ISO 10993-10:2010 protocol and the cytotoxicity tests based on the ISO 10993-5:2009 protocol. Full article
Show Figures

Figure 1

11 pages, 1339 KiB  
Article
Extraction of Individual EEG Gamma Frequencies from the Responses to Click-Based Chirp-Modulated Sounds
by Aurimas Mockevičius, Yusuke Yokota, Povilas Tarailis, Hatsunori Hasegawa, Yasushi Naruse and Inga Griškova-Bulanova
Sensors 2023, 23(5), 2826; https://doi.org/10.3390/s23052826 - 4 Mar 2023
Cited by 3 | Viewed by 3302
Abstract
Activity in the gamma range is related to many sensory and cognitive processes that are impaired in neuropsychiatric conditions. Therefore, individualized measures of gamma-band activity are considered to be potential markers that reflect the state of networks within the brain. Relatively little has [...] Read more.
Activity in the gamma range is related to many sensory and cognitive processes that are impaired in neuropsychiatric conditions. Therefore, individualized measures of gamma-band activity are considered to be potential markers that reflect the state of networks within the brain. Relatively little has been studied in respect of the individual gamma frequency (IGF) parameter. The methodology for determining the IGF is not well established. In the present work, we tested the extraction of IGFs from electroencephalogram (EEG) data in two datasets where subjects received auditory stimulation consisting of clicks with varying inter-click periods, covering a 30–60 Hz range: in 80 young subjects EEG was recorded with 64 gel-based electrodes; in 33 young subjects, EEG was recorded using three active dry electrodes. IGFs were extracted from either fifteen or three electrodes in frontocentral regions by estimating the individual-specific frequency that most consistently exhibited high phase locking during the stimulation. The method showed overall high reliability of extracted IGFs for all extraction approaches; however, averaging over channels resulted in somewhat higher reliability scores. This work demonstrates that the estimation of individual gamma frequency is possible using a limited number of both the gel and dry electrodes from responses to click-based chirp-modulated sounds. Full article
(This article belongs to the Special Issue EEG Signal Processing Techniques and Applications)
Show Figures

Figure 1

20 pages, 1977 KiB  
Review
The Feature, Performance, and Prospect of Advanced Electrodes for Electroencephalogram
by Qing Liu, Liangtao Yang, Zhilin Zhang, Hui Yang, Yi Zhang and Jinglong Wu
Biosensors 2023, 13(1), 101; https://doi.org/10.3390/bios13010101 - 6 Jan 2023
Cited by 31 | Viewed by 8079
Abstract
Recently, advanced electrodes have been developed, such as semi-dry, dry contact, dry non-contact, and microneedle array electrodes. They can overcome the issues of wet electrodes and maintain high signal quality. However, the variations in these electrodes are still unclear and not explained, and [...] Read more.
Recently, advanced electrodes have been developed, such as semi-dry, dry contact, dry non-contact, and microneedle array electrodes. They can overcome the issues of wet electrodes and maintain high signal quality. However, the variations in these electrodes are still unclear and not explained, and there is still confusion regarding the feasibility of electrodes for different application scenarios. In this review, the physical features and electroencephalogram (EEG) signal performances of these advanced EEG electrodes are introduced in view of the differences in contact between the skin and electrodes. Specifically, contact features, biofeatures, impedance, signal quality, and artifacts are discussed. The application scenarios and prospects of different types of EEG electrodes are also elucidated. Full article
(This article belongs to the Section Intelligent Biosensors and Bio-Signal Processing)
Show Figures

Figure 1

17 pages, 2623 KiB  
Article
An Open Dataset for Wearable SSVEP-Based Brain-Computer Interfaces
by Fangkun Zhu, Lu Jiang, Guoya Dong, Xiaorong Gao and Yijun Wang
Sensors 2021, 21(4), 1256; https://doi.org/10.3390/s21041256 - 10 Feb 2021
Cited by 42 | Viewed by 6986
Abstract
Brain-computer interfaces (BCIs) provide humans a new communication channel by encoding and decoding brain activities. Steady-state visual evoked potential (SSVEP)-based BCI stands out among many BCI paradigms because of its non-invasiveness, little user training, and high information transfer rate (ITR). However, the use [...] Read more.
Brain-computer interfaces (BCIs) provide humans a new communication channel by encoding and decoding brain activities. Steady-state visual evoked potential (SSVEP)-based BCI stands out among many BCI paradigms because of its non-invasiveness, little user training, and high information transfer rate (ITR). However, the use of conductive gel and bulky hardware in the traditional Electroencephalogram (EEG) method hinder the application of SSVEP-based BCIs. Besides, continuous visual stimulation in long time use will lead to visual fatigue and pose a new challenge to the practical application. This study provides an open dataset, which is collected based on a wearable SSVEP-based BCI system, and comprehensively compares the SSVEP data obtained by wet and dry electrodes. The dataset consists of 8-channel EEG data from 102 healthy subjects performing a 12-target SSVEP-based BCI task. For each subject, 10 consecutive blocks were recorded using wet and dry electrodes, respectively. The dataset can be used to investigate the performance of wet and dry electrodes in SSVEP-based BCIs. Besides, the dataset provides sufficient data for developing new target identification algorithms to improve the performance of wearable SSVEP-based BCIs. Full article
Show Figures

Figure 1

17 pages, 5201 KiB  
Article
Design and Characterization of an EEG-Hat for Reliable EEG Measurements
by Takumi Kawana, Yuri Yoshida, Yuta Kudo, Chiho Iwatani and Norihisa Miki
Micromachines 2020, 11(7), 635; https://doi.org/10.3390/mi11070635 - 28 Jun 2020
Cited by 14 | Viewed by 5240
Abstract
In this study, a new hat-type electroencephalogram (EEG) device with candle-like microneedle electrodes (CMEs), called an EEG-Hat, was designed and fabricated. CMEs are dry EEG electrodes that can measure high-quality EEG signals without skin treatment or conductive gels. One of the challenges in [...] Read more.
In this study, a new hat-type electroencephalogram (EEG) device with candle-like microneedle electrodes (CMEs), called an EEG-Hat, was designed and fabricated. CMEs are dry EEG electrodes that can measure high-quality EEG signals without skin treatment or conductive gels. One of the challenges in the measurement of high-quality EEG signals is the fixation of electrodes to the skin, i.e., the design of a good EEG headset. The CMEs were able to achieve good contact with the scalp for heads of different sizes and shapes, and the EEG-Hat has a shutter mechanism to separate the hair and ensure good contact between the CMEs and the scalp. Simultaneous measurement of EEG signals from five measurement points on the scalp was successfully conducted after a simple and brief setup process. The EEG-Hat is expected to contribute to the advancement of EEG research. Full article
Show Figures

Figure 1

16 pages, 6874 KiB  
Article
Capturing Human Perceptual and Cognitive Activities via Event-Related Potentials Measured with Candle-Like Dry Microneedle Electrodes
by Yuri Yoshida, Takumi Kawana, Eiichi Hoshino, Yasuyo Minagawa and Norihisa Miki
Micromachines 2020, 11(6), 556; https://doi.org/10.3390/mi11060556 - 30 May 2020
Cited by 7 | Viewed by 3279
Abstract
We demonstrate capture of event-related potentials (ERPs) using candle-like dry microneedle electrodes (CMEs). CMEs can record an electroencephalogram (EEG) even from hairy areas without any skin preparation, unlike conventional wet electrodes. In our previous research, we experimentally verified that CMEs can measure the [...] Read more.
We demonstrate capture of event-related potentials (ERPs) using candle-like dry microneedle electrodes (CMEs). CMEs can record an electroencephalogram (EEG) even from hairy areas without any skin preparation, unlike conventional wet electrodes. In our previous research, we experimentally verified that CMEs can measure the spontaneous potential of EEG from the hairy occipital region without preparation with a signal-to-noise ratio as good as that of the conventional wet electrodes which require skin preparation. However, these results were based on frequency-based signals, which are relatively robust compared to noise contamination, and whether CMEs are sufficiently sensitive to capture finer signals remained unclear. Here, we first experimentally verified that CMEs can extract ERPs as good as conventional wet electrodes without preparation. In the auditory oddball tasks using pure tones, P300, which represent ERPs, was extracted with a signal-to-noise ratio as good as that of conventional wet electrodes. CMEs successfully captured perceptual activities. Then, we attempted to investigate cerebral cognitive activity using ERPs. In processing the vowel and prosody in auditory stimuli such as /itta/, /itte/, and /itta?/, laterality was observed that originated from the locations responsible for the process in near-infrared spectroscopy (NIRS) and magnetoencephalography experiments. We simultaneously measured ERPs with CMEs and NIRS in the oddball tasks using the three words. Laterality appeared in NIRS for six of 10 participants, although laterality was not clearly shown in the results, suggesting that EEGs have a limitation of poor spatial resolution. On the other hand, successful capturing of MMN and P300 using CMEs that do not require skin preparation may be readily applicable for real-time applications of human perceptual activities. Full article
Show Figures

Figure 1

10 pages, 3221 KiB  
Article
A Dry Electrode Cap and Its Application in a Steady-State Visual Evoked Potential-Based Brain–Computer Interface
by Xiaoting Wu, Li Zheng, Lu Jiang, Xiaoshan Huang, Yuanyuan Liu, Lihua Xing, Xiao Xing, Yijun Wang, Weihua Pei, Xiaowei Yang, Zhiduo Liu, Chunrong Wei, Yamin Li, Miao Yuan and Hongda Chen
Electronics 2019, 8(10), 1080; https://doi.org/10.3390/electronics8101080 - 23 Sep 2019
Cited by 9 | Viewed by 4773
Abstract
The wearable electroencephalogram (EEG) dry electrode acquisition system has shown great application prospects in mental state monitoring, the brain–computer interface (BCI), and other fields due to advantages such as being small in volume, light weight, and a ready-to-use facility. This study demonstrates a [...] Read more.
The wearable electroencephalogram (EEG) dry electrode acquisition system has shown great application prospects in mental state monitoring, the brain–computer interface (BCI), and other fields due to advantages such as being small in volume, light weight, and a ready-to-use facility. This study demonstrates a novel EEG cap with concise structure, easy adjustment size, as well as independently adjustable electrodes. The cap can be rapidly worn and adjusted in both horizontal and vertical dimensions. The dry electrodes on it can be adjusted independently to fit the scalp as quickly as possible. The accuracy of the BCI test employing this device is higher than when employing a headband. The proposed EEG cap makes adjustment easier and the contact impedance of the dry electrodes more uniform. Full article
Show Figures

Figure 1

Back to TopTop