Electroencephalography (EEG) has become more popular, and as a result, the market grows with new EEG products. The new EEG solutions offer higher mobility, easier application, and lower price. One of such devices that recently became popular is Emotiv EEG. It has been already tested in various applications concerning brain-computer interfaces, neuromarketing, language processing, and detection of the P-300 component, with a general result that it is capable of recording satisfying research data. However, no one has tested and described its usefulness in long-term research. This article presents experience from using Emotiv EEG in two research projects that involved 39 subjects for 22 sessions. Emotiv EEG has significant technical issues concerning the quality of its screw threads. Two complete and successful solutions to this problem are described.
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Despite the quick development of medicine and associated medical technology, there are still many patients with very severe neurological deficits who need far more sophisticated solutions, such as brain computer interfaces (BCIs). Our research aims at becoming familiar with BCI technology and the assessment of the possibilities of selected subjects in the area of P300-based BCI. An indirect aim is a discussion on the procedures of patient preparation for BCI installation, possible threats and limitations. Our research presents one of the possible efforts towards better documentation of investigating neural correlates of brain processing.
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This paper focuses on finding the most efficinet way of performing local and remote computations with web appliacation based on ActionScript language. Tests involve comparsion of several scenarions which uses pure ActionScript, ActionScript with Alchemy project and ActionScript connecting with C application over AMF protocol and with FileReference class.
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The paper presents EEG signal visualisation software designed for the Mindset MS-1000 EEG 16-channel device, manufactured by Nolan Computer Systems. The software is designed to work system independently and be accessible via web browsers. The presented application was developed in Adobe Flex technology with external Papervision3D library. It provides complete visualisation solutions such as navigable EEG chart or two separated 3D head models with applied EEG data.
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