Computational Biology and Bioinformatics

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Fundamental Engineering for Brain-Computer Interfacing (BCI): Initiative for Neuron-Command Operating Devices

Received: 23 March 2017    Accepted: 14 April 2017    Published: 07 November 2017
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Abstract

For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain functionmight provide a new non-muscular channel for sending messages and commands to the external world – a brain–computer interface (BCI) [4]. Over the past 15 years, productive BCI research programs have arisen [4]. Encouraged by new understanding of brain function, by the advent ofpowerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programsconcentrate on developing new augmentative communication and control technology for those with severe neuromuscular disorders, such asamyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury [34]. The immediate goal is to provide these users, who may be completelyparalyzed, or ‘locked in’, with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses [4]. Present-day BCIs determine the intent of the user from a variety of different electrophysiologicalsignals [4]. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronalactivity recorded by implanted electrodes [4]. They are translated in real-time into commands that operate a computer display or other device [4]. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals [4]. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance [29]. Current BCIs havemaximum information transfer rates up to 10–25 bits/min [4]. This limited capacity can be valuable for people whose severe disabilities preventthem from using conventional augmentative communication methods [4].

DOI 10.11648/j.cbb.20170504.12
Published in Computational Biology and Bioinformatics (Volume 5, Issue 4, August 2017)
Page(s) 50-56
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

NCOD, BCI, Neuron -Engineering, Brain-Interfacing, Biomedical Interfacing

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Author Information
  • Institute of Management & Science (IMS), Sakegaon, Bhusawal, M.S, India

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    Md. Sadique Shaikh. (2017). Fundamental Engineering for Brain-Computer Interfacing (BCI): Initiative for Neuron-Command Operating Devices. Computational Biology and Bioinformatics, 5(4), 50-56. https://doi.org/10.11648/j.cbb.20170504.12

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    Md. Sadique Shaikh. Fundamental Engineering for Brain-Computer Interfacing (BCI): Initiative for Neuron-Command Operating Devices. Comput. Biol. Bioinform. 2017, 5(4), 50-56. doi: 10.11648/j.cbb.20170504.12

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    Md. Sadique Shaikh. Fundamental Engineering for Brain-Computer Interfacing (BCI): Initiative for Neuron-Command Operating Devices. Comput Biol Bioinform. 2017;5(4):50-56. doi: 10.11648/j.cbb.20170504.12

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  • @article{10.11648/j.cbb.20170504.12,
      author = {Md. Sadique Shaikh},
      title = {Fundamental Engineering for Brain-Computer Interfacing (BCI): Initiative for Neuron-Command Operating Devices},
      journal = {Computational Biology and Bioinformatics},
      volume = {5},
      number = {4},
      pages = {50-56},
      doi = {10.11648/j.cbb.20170504.12},
      url = {https://doi.org/10.11648/j.cbb.20170504.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.cbb.20170504.12},
      abstract = {For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain functionmight provide a new non-muscular channel for sending messages and commands to the external world – a brain–computer interface (BCI) [4]. Over the past 15 years, productive BCI research programs have arisen [4]. Encouraged by new understanding of brain function, by the advent ofpowerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programsconcentrate on developing new augmentative communication and control technology for those with severe neuromuscular disorders, such asamyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury [34]. The immediate goal is to provide these users, who may be completelyparalyzed, or ‘locked in’, with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses [4]. Present-day BCIs determine the intent of the user from a variety of different electrophysiologicalsignals [4]. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronalactivity recorded by implanted electrodes [4]. They are translated in real-time into commands that operate a computer display or other device [4]. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals [4]. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance [29]. Current BCIs havemaximum information transfer rates up to 10–25 bits/min [4]. This limited capacity can be valuable for people whose severe disabilities preventthem from using conventional augmentative communication methods [4].},
     year = {2017}
    }
    

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