Volume 13 Number 7 (Jul. 2018)
Home > Archive > 2018 > Volume 13 Number 7 (Jul. 2018) >
JSW 2018 Vol.13(7): 407-413 ISSN: 1796-217X
doi: 10.17706/jsw.13.7.407-413

One Approach for Identification of Brain Signals for Smart Devices Control

Georgi P. Dimitrov1*, Galina S. Panayotova1, Eugenia Kovatcheva1, Daniela Borissova2, and Pavel Petrov3
1University of Library Studies and Information Technologies, Sofia, 1712, Bulgaria
2Institute of Information and Communication Technologies at Bulgarian Academy of Sciences,Acad. G. Bonchev St., Bl. 2, 1113 Sofia, Bulgaria
3University of Economics - Varna, Knyaz Boris I Blvd. 77, 9002 Varna, Bulgaria

Abstract—Nowadays the UX design become on a next level. Together with new way of interaction are introduced as finger and hand movement. The technology offer and thought-driven approach with so called brain-computer interface (BCI). This possibility opens new challenges for uses as well as for designers and researchers. More than 15 years there are devices for brain signal interception, such as EMotiv Epoc, Neurosky headset and others. The reliable translation of user commands to the app on a global scale, with no leaps in advancement for its lifetime, is a challenge. It is still un-solve for modern scientists and software developers. Success requires the effective interaction of many adaptive controllers: the user's brain, which produces brain activity that encodes intent; the BCI system, which translates that activity into the digital signals; the accuracy of aforementioned system, computer algorithms to translate the brain signals to commands. In order to find out this complex and monumental task, many teams are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. Rarely there are publications, in which are described the used methods, steps and algorithms for discerning varying commands, words, signals and etc. This article describes one approach to the retrieval, analysis and processing of the received signals. These data are the result of researching the capabilities of Arduino robot management through the brain signals received by BCI.

Index Terms—ntegrated information systems, Brain Computer Interface, BCI, BIG Data, data processing, sensors, EMotiv


Cite: Georgi P. Dimitrov, Galina S. Panayotova, Eugenia Kovatcheva, Daniela Borissova, and Pavel Petrov, "One Approach for Identification of Brain Signals for Smart Devices Control," Journal of Software vol. 13, no. 7, pp. 407-413, 2018.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]