Comparison of foam-based and spring-loaded dry EEG electrodes with wet electrodes in resting and moving conditions

Yeung, Arnold; Garudadri, Harinath; Toen, Carolyn Van; Mercier, Patrick P.; Balkan, Ozgur; Makeig, Scott; Virji‐Babul, Naznin

doi:10.1109/embc.2015.7320036

Cited by 12 publications

(14 citation statements)

References 11 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are other means to compare EEG systems, for example, the correlation of waveforms from two different EEG systems during a simultaneous recording from electrodes located near each other (Gargiulo et al, 2010; Yeung et al, 2015). Many mobile EEG systems have a rigid montage, and it is not possible to overlay montages of two different EEG systems.…”

Section: Discussionmentioning

confidence: 99%

“…The developed benchmark of six paradigms and yielded results can be used for evaluation of new EEG systems. In contrast to other studies (Gargiulo et al, 2010; Guger et al, 2012; Liao et al, 2012; De Vos et al, 2014; Yeung et al, 2015; Oliveira et al, 2016b), which compare EEG signals from different systems, we match the difference between EEG systems to other factors of variance, like subjects and sessions, in order to estimate the importance of the difference between EEG systems. We also demonstrated the mesh-head-model interpolation approach, which addresses the issue of not overlapping EEG montages of different EEG systems.…”

Section: Discussionmentioning

confidence: 99%

“…Another study examined the correlation of signals from dry foam-based EEG sensors and wet EEG sensors, as well as the impedance at the sensor-skin contact during long-term EEG measurements (Liao et al, 2012). Yeung et al (2015) completed a comparison of foam-based and spring-loaded dry EEG electrodes using three experimental paradigms by linear correlation analyses. Additional studies have looked at the application-based performance using P300 brain-computer interfaces with dry and gel-based electrodes (Guger et al, 2012; De Vos et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

Melnik

Legkov

Izdebski

et al. 2017

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

Melnik

Legkov

Izdebski

et al. 2017

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Since then, a wide number of materials have been considered for making dry EEG electrodes [19,20,21,22]. The commercially available g.SAHARA electrodes [9,23] use gold and a similar closely-positioned impedance-converting amplifier approach.…”

Section: Electrode Materials and Chemistrymentioning

confidence: 99%

3D Printed Dry EEG Electrodes

Krachunov

Casson

2016

Sensors

View full text Add to dashboard Cite

Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

show abstract

“…Another recent study from Wang et al compared power spectra and time-frequency maps (spectrograms) between the two systems to evaluate the feasibility of novel semi-dry electrodes (Wang et al, 2016 ). Although these novel system designs show promise in a controlled laboratory setting, few studies have shown the feasibility of individuals using these systems in a dynamic, real-world environment (Gargiulo et al, 2008 ; Liao et al, 2012 ; Lin et al, 2013 ; Yeung et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Deployment of Mobile EEG Technology in an Art Museum Setting: Evaluation of Signal Quality and Usability

Cruz-Garza

Brantley

Nakagome

et al. 2017

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Electroencephalography (EEG) has emerged as a powerful tool for quantitatively studying the brain that enables natural and mobile experiments. Recent advances in EEG have allowed for the use of dry electrodes that do not require a conductive medium between the recording electrode and the scalp. The overall goal of this research was to gain an understanding of the overall usability and signal quality of dry EEG headsets compared to traditional gel-based systems in an unconstrained environment. EEG was used to collect Mobile Brain-body Imaging (MoBI) data from 432 people as they experienced an art exhibit in a public museum. The subjects were instrumented with either one of four dry electrode EEG systems or a conventional gel electrode EEG system. Each of the systems was evaluated based on the signal quality and usability in a real-world setting. First, we describe the various artifacts that were characteristic of each of the systems. Second, we report on each system's usability and their limitations in a mobile setting. Third, to evaluate signal quality for task discrimination and characterization, we employed a data driven clustering approach on the data from 134 of the 432 subjects (those with reliable location tracking information and usable EEG data) to evaluate the power spectral density (PSD) content of the EEG recordings. The experiment consisted of a baseline condition in which the subjects sat quietly facing a white wall for 1 min. Subsequently, the participants were encouraged to explore the exhibit for as long as they wished (piece-viewing). No constraints were placed upon the individual in relation to action, time, or navigation of the exhibit. In this freely-behaving approach, the EEG systems varied in their capacity to record characteristic modulations in the EEG data, with the gel-based system more clearly capturing stereotypical alpha and beta-band modulations.

show abstract

Comparison of foam-based and spring-loaded dry EEG electrodes with wet electrodes in resting and moving conditions

Cited by 12 publications

References 11 publications

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

3D Printed Dry EEG Electrodes

Deployment of Mobile EEG Technology in an Art Museum Setting: Evaluation of Signal Quality and Usability

Contact Info

Product

Resources

About