Edited by: Cuntai Guan, Institute for Infocomm Research, Singapore
Reviewed by: Dennis J. McFarland, Wadsworth Center for Laboratories and Research, USA; Michal Lavidor, Bar-Ilan University, Israel
*Correspondence: Christoph Guger, g.tec medical engineering GmbH, Guger Technologies OG, Herbersteinstrasse 60, A8010 Graz, Styria, Austria. e-mail:
This article was submitted to Frontiers in Neuroprosthetics, a specialty of Frontiers in Neuroscience.
This is an open-access article distributed under the terms of the
Most brain–computer interfaces (BCIs) rely on one of three types of signals in the electroencephalogram (EEG): P300s, steady-state visually evoked potentials, and event-related desynchronization. EEG is typically recorded non-invasively with electrodes mounted on the human scalp using conductive electrode gel for optimal impedance and data quality. The use of electrode gel entails serious problems that are especially pronounced in real-world settings when experts are not available. Some recent work has introduced dry electrode systems that do not require gel, but often introduce new problems such as comfort and signal quality. The principal goal of this study was to assess a new dry electrode BCI system in a very common task: spelling with a P300 BCI. A total of 23 subjects used a P300 BCI to spell the word “LUCAS” while receiving real-time, closed-loop feedback. The dry system yielded classification accuracies that were similar to those obtained with gel systems. All subjects completed a questionnaire after data recording, and all subjects stated that the dry system was not uncomfortable. This is the first field validation of a dry electrode P300 BCI system, and paves the way for new research and development with EEG recording systems that are much more practical and convenient in field settings than conventional systems.
Brain–computer interfaces (BCIs) allow communication without movement. In a typical BCI, a user performs voluntary mental tasks that each produce distinct patterns of electrical activity in the electroencephalogram (EEG). Automated signal processing software tries to identify which mental tasks a user performed at specific times and thereby infer user intent. Most modern BCIs rely on one of three types of mental tasks, which are associated with different types of brain activity (Wolpaw et al.,
Imagined movement, which produces event-related desynchronization (ERD; Guger et al.,
Attention to oscillating visual stimuli, which produces steady-state visual evoked potentials (SSVEP; Friman et al.,
Attention to transient stimuli, which produces the P300 event-related potential (ERP; Sellers et al.,
Despite some delightfully strident arguments within the research community, there is no general agreement on which approach is best. Instead, different BCIs are better suited to different users, needs, environments, applications, and other parameters. The main drawback of the P300 BCI is that users must pay attention to specific events, usually flashes on a monitor. Hence, users must pace themselves according to the system, and may find the flashes annoying. On the other hand, P300 BCIs seem to work for nearly all healthy users, unlike (at least) ERD BCIs (Guger et al.,
Most P300 BCIs allow users to choose one target from several options, such as letters or numbers presented on a monitor (Farwell and Donchin,
However, like most BCIs, P300 BCIs are hampered by the need for conductive gel to get a good contact between each electrode and the scalp. Preparing a subject for conventional EEG recording requires abrading the skin under each electrode, positioning each electrode over the abraded area, and squirting electrode gel underneath each electrode. Getting a good contact between each electrode and the scalp usually requires further skin abrasion and application of gel. The gel is uncomfortable to many subjects, and must be washed out of both the cap and hair later. This procedure greatly increases the time and inconvenience needed for any EEG recording session. Also, after a few hours of use, the gel may dry, and new gel must be applied (Ko and Hynecek,
These problems reduce the appeal of EEG-based technologies to most users, and can be especially pronounced for severely disabled users – even though these are the people who need BCIs most. Some conditions can increase skin sensitivity, making the skin abrasion process more painful. Since some of these patients cannot communicate without a BCI, they may have no way to convey their distress during preparation. Hence, working with gel-based electrodes increases dependence on friends, family, or other caretakers.
Numerous recent articles that survey different end users have further confirmed that dry electrodes are a very high priority. Casson et al. (
Since dry electrodes can substantially simplify EEG recording, and are identified as important across numerous surveys, there should be a strong interest in them. Indeed, numerous articles over many years have explored dry electrodes to record EEG and other physiological signals (e.g., Roman,
There are two general approaches to dry electrodes, each with distinct problems (Portnoy et al.,
Recently, interest in dry electrodes has increased considerably. A PubMed search on February 1, 2012 for “dry electrode EEG” revealed 37 articles; only five were published before 2000, and another five were published before 2007. An otherwise identical search that replaced “EEG” with “BCI” found six articles, all published 2007 or later. Many companies are also producing dry electrode systems. Most sales are simple toy systems that detect drowsiness or fatigue with one electrode, unlike more complex multi-electrode systems that detect conventional BCI signals such as P300, SSVEP, and ERD.
Of the six journal publications that include “EEG” and “BCI,” there seems to be a dearth of P300 BCI work. Carabalona et al. (
In addition to these journal publications, some conference papers have presented dry electrode systems. For example, our 2007 conference paper evaluated a dry electrode system in a gaming context, and a later conference paper used the same company’s system in a P300 copy-spelling task (Trejo et al.,
All of these factors underscore the opportunity and need to explore well-established P300 methods with dry electrodes. The primary goal of this study was to assess a new dry electrode system in an otherwise conventional P300 BCI. A total of 23 subjects used a P300 BCI that was very much like other P300 BCIs in terms of the display, task, paradigm, signal processing, and other details. We present conventional analyses such as accuracy as well as subjective report regarding the comfort of the dry electrode system.
Twenty-three subjects (six female, age: 22–60) participated in the study. All subjects were free of medication, had normal vision or vision corrected to normal, and no history of central nervous system abnormalities. All subjects provided informed consent before participating in the study. The procedure complied with the ethical review procedures within the BrainAble project. Subjects were prepared for recording with the dry electrode system, using eight recording sites plus a reference and ground as shown in Figure
Subjects sat in front of a laptop computer and were instructed to relax and remain as still as possible. The laptop used the intendiX row/column (RC) speller shown in Figure
After each trial, the signal processing software extracted individual ERPs from 100 ms before to 700 ms after each flash. The 100-ms time segment before each flash was used for baseline correction. While subjects spelled the word “WATER,” they did not receive any feedback. Next, the system performed linear discriminant analysis (LDA) based on these ERPs to create the weight vector for the upcoming online trials.
Next, the subject was asked to spell the word “LUCAS” in the same fashion as “WATER,” except that the system used the updated classifier and provided real-time feedback. Only the results of the effort to spell “LUCAS” are reported in this paper. After each trial, the intendiX system presented the target character on the top of the monitor. The delay between the last row or column flash and the presentation of this feedback was less than 1 s. After the feedback was presented, there was a delay of 2.15 s before the subject was cued to the next target character, and the highlighting sequence began again.
At the end of the recording procedure, some subjects chose to continue using the system in “free spelling” mode, in which they spelled text of their choosing. The data from these runs are not presented here, but Figure
After this procedure was complete, one of the 23 subjects then repeated the procedure using gel-based electrodes as described below. This additional recording was performed so we could present a direct, within-subject comparison of the raw EEG, ERPs, and BCI performance resulting from dry vs. gel electrodes, shown in Figures
Figure
Electroencephalogram data were acquired using a g.USBamp (24 Bit biosignal amplification unit, g.tec medical engineering GmbH, Austria) with a sampling frequency of 256 Hz. The data were then converted to double precision, bandpass filtered between 0.5 and 30 Hz, and then down-sampled to 64 Hz. The ground electrode was mounted over the left mastoid and the reference was mounted over the right mastoid; for both positions disposable pre-gelled electrode pads were used. EEG electrodes were fixed to an EEG electrode cap (g.GAMMAcap) according to the extended international 10/20 electrode system. EEG recordings based on gel electrodes were done with the g.BUTTERfly electrode (golden ring electrode type with a hole in the middle to inject the gel); EEG recordings based on dry electrodes instead used the g.SAHARA electrode (eight gold-coated pins with 7 mm/16 mm length mounted in a circular arrangement, diameter 15 mm). Both types of electrodes are active EEG electrodes with a small preamplifier located in the electrode itself. Both types of electrodes do not penetrate the epidermis. The tips of the electrode contacts in the g.SAHARA system are smooth, not pointed, to avoid discomfort.
Before presenting results with the P300 speller, we first address the
The next question is whether the ERPs look similar across both electrode types. Figure
Table
Row-column speller classification accuracy in % | Gel electrodes ( |
Dry electrodes ( |
---|---|---|
100 | 72.8 | 69.6 |
80–100 | 88.9 | 87.0 |
60–79 | 6.2 | 8.7 |
40–59 | 3.7 | 4.4 |
20–39 | 0.0 | 0 |
0–19 | 1.2 | 0 |
Average accuracy of all subjects | 91.0 ± 18.5 | 90.4 ± 17.2 |
Table
There is one noteworthy paradigmatic difference that affects classification accuracy. The 2009 study used a display with 36 characters. Hence, chance performance was one in 36, or about 2.8%. The present study instead had a vocabulary of 50 characters, corresponding to 2% chance performance. Therefore, in the 2009 study, correct classification due to chance was slightly more likely than in the present study.
The present study flashed each character 15 times, consistent with canonical work (Farwell and Donchin,
All 23 subjects were asked whether the dry electrode system was uncomfortable in a short questionnaire. None of the subjects reported any discomfort through these questionnaires, nor did they complain in any other way. In the 2009 study none of the subjects reported any discomfort from the g.BUTTERFLY electrodes that were used.
Furthermore, g.tec hosts several workshops a year, in which hundreds of people have used g.BUTTERFLY electrodes, and dozens have used the g.SAHARA electrodes. None of these participants have reported any discomfort with either electrode. Hence, at least with the conditions used in this study and g.tec workshops, both electrode types were not uncomfortable.
This is the first journal publication to show that dry electrodes can yield performance comparable to gel electrodes with a P300 BCI. This is an important outcome, given the promise and prominence of both dry electrodes and P300 BCIs. Subjects did not consider the dry electrode system uncomfortable, and it required no gel and reduced preparation time. Although the dry electrode system might be more prone to movement artifact and ambient electrostatic charges, these were not a problem in the present study. Overall, the new system is generally comparable to or better than gel electrodes in many ways.
This work is also important because it demonstrates that the dry electrode system can function in a relatively unconstrained field setting. Dry electrodes typically entail much higher impedance values than gel electrodes. This is the main reason why gel is so common; the gel provides contact between the scalp and each electrode that greatly reduces impedance. Otherwise, high impedance will impair signal quality and increase vulnerability to electrical artifact, such as from external devices or movement. The dry electrode system allows good performance despite high impedances by using multiple gold-coated pins in each electrode, as well as an integrated amplifier within each electrode.
Interestingly, although the dry electrode system resulted in EEG data, ERPs, and BCI accuracy comparable to gel electrodes, there were notable differences. The average peak P300 amplitude was lower in the present study. The dry electrodes showed higher signal drifts below 3 Hz than gel based electrodes. Neither of these difference had a notable effect on classification accuracy. However, these differences might be relevant for other types of BCIs. For example, BCIs that rely on slow cortical potential changes (Birbaumer et al.,
Although this is a promising start, there are many issues that still need to be explored. As noted, dry electrodes need to be explored with a much wider variety of BCI systems, with different mental tasks, EEG signals, and other details. Comfort and other subjective factors should be assessed in other circumstances, such as with electrodes mounted in other headwear, tasks requiring physical movement, and long-term use. All of the subjects in this study, like all published dry electrode studies, were healthy. Dry electrodes should be validated with persons with severe disabilities, since they often need BCIs more than healthy users. With some such users, special concerns (such as fasciculations that produce uncontrolled movement) might be especially problematic for dry electrodes. We also recommend focusing on other comparisons between dry and gel electrodes. While accuracy and comfort are very important, research should also parametrically compare preparation time, reliance on outside support, and other factors. These may be more difficult to paradigmatically assess, but are critical factors in BCI adoption (Allison,
The Christoph Guger, Gunther Krausz, and Guenter Edlinger are full-time employees of g.tec medical engineering GmbH, Guger Technologies OG, and the Christoph Guger and Guenter Edlinger are its co-CEOs.
This work was funded by EC projects: CSI, ALIAS, Brainable, Decoder, and Better.