Abstract
Original language | Undefined |
---|---|
Pages (from-to) | 1-10 |
Number of pages | 10 |
Journal | Frontiers in neuroscience |
Volume | 5 |
Issue number | 53 |
DOIs | |
Publication status | Published - 26 May 2011 |
Keywords
- EWI-21579
- EEG
- Brain-Computer Interface
- IR-79822
- Sensors
- METIS-285154
- BCI
Cite this
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A Dry EEG-System for Scientific Research and Brain–Computer Interfaces. / Zander, Thorsten Oliver; Lehne, Moritz; Ihme, Klas; Jatzev, Sabine; Correia, Joao; Kothe, Christian; Picht, Bernd; Nijboer, Femke.
In: Frontiers in neuroscience, Vol. 5, No. 53, 26.05.2011, p. 1-10.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A Dry EEG-System for Scientific Research and Brain–Computer Interfaces
AU - Zander, Thorsten Oliver
AU - Lehne, Moritz
AU - Ihme, Klas
AU - Jatzev, Sabine
AU - Correia, Joao
AU - Kothe, Christian
AU - Picht, Bernd
AU - Nijboer, Femke
N1 - eemcs-eprint-21579
PY - 2011/5/26
Y1 - 2011/5/26
N2 - Although it ranks among the oldest tools in neuroscientific research, electroencephalography (EEG) still forms the method of choice in a wide variety of clinical and research applications. In the context of brain–computer interfacing (BCI), EEG recently has become a tool to enhance human–machine interaction. EEG could be employed in a wider range of environments, especially for the use of BCI systems in a clinical context or at the homes of patients. However, the application of EEG in these contexts is impeded by the cumbersome preparation of the electrodes with conductive gel that is necessary to lower the impedance between electrodes and scalp. Dry electrodes could provide a solution to this barrier and allow for EEG applications outside the laboratory. In addition, dry electrodes may reduce the time needed for neurological exams in clinical practice. This study evaluates a prototype of a three-channel dry electrode EEG system, comparing it to state-of-the-art conventional EEG electrodes. Two experimental paradigms were used: first, event-related potentials (ERP) were investigated with a variant of the oddball paradigm. Second, features of the frequency domain were compared by a paradigm inducing occipital alpha. Furthermore, both paradigms were used to evaluate BCI classification accuracies of both EEG systems. Amplitude and temporal structure of ERPs as well as features in the frequency domain did not differ significantly between the EEG systems. BCI classification accuracies were equally high in both systems when the frequency domain was considered. With respect to the oddball classification accuracy, there were slight differences between the wet and dry electrode systems. We conclude that the tested dry electrodes were capable to detect EEG signals with good quality and that these signals can be used for research or BCI applications. Easy to handle electrodes may help to foster the use of EEG among a wider range of potential users.
AB - Although it ranks among the oldest tools in neuroscientific research, electroencephalography (EEG) still forms the method of choice in a wide variety of clinical and research applications. In the context of brain–computer interfacing (BCI), EEG recently has become a tool to enhance human–machine interaction. EEG could be employed in a wider range of environments, especially for the use of BCI systems in a clinical context or at the homes of patients. However, the application of EEG in these contexts is impeded by the cumbersome preparation of the electrodes with conductive gel that is necessary to lower the impedance between electrodes and scalp. Dry electrodes could provide a solution to this barrier and allow for EEG applications outside the laboratory. In addition, dry electrodes may reduce the time needed for neurological exams in clinical practice. This study evaluates a prototype of a three-channel dry electrode EEG system, comparing it to state-of-the-art conventional EEG electrodes. Two experimental paradigms were used: first, event-related potentials (ERP) were investigated with a variant of the oddball paradigm. Second, features of the frequency domain were compared by a paradigm inducing occipital alpha. Furthermore, both paradigms were used to evaluate BCI classification accuracies of both EEG systems. Amplitude and temporal structure of ERPs as well as features in the frequency domain did not differ significantly between the EEG systems. BCI classification accuracies were equally high in both systems when the frequency domain was considered. With respect to the oddball classification accuracy, there were slight differences between the wet and dry electrode systems. We conclude that the tested dry electrodes were capable to detect EEG signals with good quality and that these signals can be used for research or BCI applications. Easy to handle electrodes may help to foster the use of EEG among a wider range of potential users.
KW - EWI-21579
KW - EEG
KW - Brain-Computer Interface
KW - IR-79822
KW - Sensors
KW - METIS-285154
KW - BCI
U2 - 10.3389/fnins.2011.00053
DO - 10.3389/fnins.2011.00053
M3 - Article
VL - 5
SP - 1
EP - 10
JO - Frontiers in neuroscience
JF - Frontiers in neuroscience
SN - 1662-4548
IS - 53
ER -