Abstract
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.
Highlights
To address the issues that arise with our aging society and its related health problems it is likely that we will need technologies to aid persons in their daily work and life, to help persons stay physically and mentally fit as long as possible and have early detection of diseases or disorders. Chatterjee and Price (2009) argue that these technologies will need to be persuasive in order for users to adhere to their use
With the emergence of the new research field of brain–computer interfaces (BCIs), the EEG was applied as an input channel to control assistive technology for persons with physical disabilities rather than as a research tool (Wolpaw et al, 2002; Dornhege et al, 2007)
The aim of the current study is to evaluate the signal quality of the dry electrode system for EEG analysis and for BCI applications
Summary
Chatterjee and Price (2009) argue that these technologies will need to be persuasive in order for users to adhere to their use. They predict that more user-aware, ambient-aware, and context-aware smart technologies can be expected that will increase persuasion. One of the traditional tools to assess user states and users’ intentions is the use of electroencephalography (EEG) as one of the oldest imaging techniques used in clinical diagnosis and cognitive neuroscience. With the emergence of the new research field of brain–computer interfaces (BCIs), the EEG was applied as an input channel to control assistive technology for persons with physical disabilities rather than as a research tool (Wolpaw et al, 2002; Dornhege et al, 2007). Features of the EEG are used as input to model user’s states to adapt human–machine interaction (HMI, Krepki et al, 2007; Cutrell and Tan, 2008; Müller et al, 2008; Zander et al, 2008, 2010; Williamson et al, 2009; Blankertz et al, 2010a; Zander and Kothe, 2011)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
