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Sensors 2017, 17(7), 1525;

Characterizing Computer Access Using a One-Channel EEG Wireless Sensor

Departamento de Tecnología Electrónica, ETS Ingeniería Informática, Universidad de Sevilla, Campus de Reina Mercedes, Sevilla 41012, Spain
ASPACE Sevilla, Dos Hermanas, Sevilla 41704, Spain
Current address: ETS Ingeniería Informática, Campus de Reina Mercedes sn, Sevilla 41012, Spain
Author to whom correspondence should be addressed.
Received: 1 June 2017 / Revised: 22 June 2017 / Accepted: 26 June 2017 / Published: 29 June 2017
(This article belongs to the Section Physical Sensors)
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This work studies the feasibility of using mental attention to access a computer. Brain activity was measured with an electrode placed at the Fp1 position and the reference on the left ear; seven normally developed people and three subjects with cerebral palsy (CP) took part in the experimentation. They were asked to keep their attention high and low for as long as possible during several trials. We recorded attention levels and power bands conveyed by the sensor, but only the first was used for feedback purposes. All of the information was statistically analyzed to find the most significant parameters and a classifier based on linear discriminant analysis (LDA) was also set up. In addition, 60% of the participants were potential users of this technology with an accuracy of over 70%. Including power bands in the classifier did not improve the accuracy in discriminating between the two attentional states. For most people, the best results were obtained by using only the attention indicator in classification. Tiredness was higher in the group with disabilities (2.7 in a scale of 3) than in the other (1.5 in the same scale); and modulating the attention to access a communication board requires that it does not contain many pictograms (between 4 and 7) on screen and has a scanning period of a relatively high t s c a n 10 s. The information transfer rate (ITR) is similar to the one obtained by other brain computer interfaces (BCI), like those based on sensorimotor rhythms (SMR) or slow cortical potentials (SCP), and makes it suitable as an eye-gaze independent BCI. View Full-Text
Keywords: cerebral palsy; attention; brain computer interface; wireless EEG sensor; linear discriminant analysis cerebral palsy; attention; brain computer interface; wireless EEG sensor; linear discriminant analysis

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Molina-Cantero, A.J.; Guerrero-Cubero, J.; Gómez-González, I.M.; Merino-Monge, M.; Silva-Silva, J.I. Characterizing Computer Access Using a One-Channel EEG Wireless Sensor. Sensors 2017, 17, 1525.

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