Mobile Brain-Computer Interface for the Cloud-Computing of Neurophysiological Responses
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Minguillón Campos, JesúsEditorial
Universidad de Granada
Departamento
Universidad de Granada.Materia
Bioinformática Neurofisiología
Materia UDC
681.3 3304 1203
Date
2018Fecha lectura
2018-11-22Referencia bibliográfica
Minguillón Campos, Jesús. Mobile Brain-Computer Interface for the Cloud-Computing of Neurophysiological Responses. Granada: Universidad de Granada, 2018. [http://hdl.handle.net/10481/54077]
Sponsorship
Tesis Univ. Granada. Programa de Doctorado en Tecnologías de la Información y la Comunicación; This thesis has been mostly supported by the Junta of Andalucia (Spain) [grant P11-TIC-7983], the Ministry of Economy and Competitiveness (Spain) [TIN2015- 67020P] and the Spanish National Youth Guarantee Implementation Plan (Spain), co- nanced by the European Regional Development Fund (ERDF). Additional funding has been received from the Ministry of Economy and Competitiveness (Spain) [grant DPI2015-69098-REDT], the Orden Hospitalaria San Juan de Dios (Spain) and the Vice-Rectorate for Internationalization of the University of Granada (Spain) [research stay grant].Abstract
Thanks to the development of mobile technology and real-time capable algorithms,
traditional BCIs coexist with new mobile-BCI-based applications nowadays. The
aim of this thesis was to research and develop mobile-BCI-based applications and
to apply them to field-research studies.
First, hardware and software requirements for mobile-BCI-based applications have
been analyzed. In particular, the limitations of current wireless and low-cost EEG
acquisition systems have been reviewed. In addition, the use of signal processing
algorithms (artifact removal, feature extraction and classification) in mobile BCIs
has been investigated. These requirements have been used to develop a portable,
wireless, low-cost hardware/software system for real-time acquisition and processing
of biosignals (i.e., RABio w8). The developed system improves the existing
commercial systems in terms of cost, configurability, portability and usability, being
a reliable and useful instrument for the research community and, in the future,
for the general public.
The next stage has been to develop several functional and ubiquitous out-of-lab
applications based on mobile BCI and on cloud-computing. In particular, for the
detection and training of attention, for the assessment and detection of stress level,
for the generation of secure passwords through EEG signals and for the diagnosis
of visual-system-related pathologies through visual evoked potentials. In most
cases the RABio w8 system was used. These applications have demonstrated a
considerable potential, with the option of having a relevant impact on society.
Finally, all the above has been applied to field-research studies related to physiological,
cognitive and affective computing. Specifically, in studies related to attention,
stress, EEG-based password generation and visual evoked potentials, among others.
Valuable scientific results have been obtained from the field-research studies, thus
proving the usefulness of the developed technology, and giving rise to a considerable
number of publications in international journals with impact factor and congresses.
In conclusion, the results of this thesis could generate a relevant impact on the research
community and, potentially, on various areas of society including work and
military defense, education, mental health, sports and e-sports, art and communications.