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      Non-invasive EEG-based BCI spellers from the beginning to today: a mini-review

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          Abstract

          The defeat of the central motor neuron leads to the motor disorders. Patients lose the ability to control voluntary muscles, for example, of the upper limbs, which introduces a fundamental dissonance in the possibility of daily use of a computer or smartphone. As a result, the patients lose the ability to communicate with other people. The article presents the most popular paradigms used in the brain-computer-interface speller system and designed for typing by people with severe forms of the movement disorders. Brain-computer interfaces (BCIs) have emerged as a promising technology for individuals with communication impairments. BCI-spellers are systems that enable users to spell words by selecting letters on a computer screen using their brain activity. There are three main types of BCI-spellers: P300, motor imagery (MI), and steady-state visual evoked potential (SSVEP). However, each type has its own limitations, which has led to the development of hybrid BCI-spellers that combine the strengths of multiple types. Hybrid BCI-spellers can improve accuracy and reduce the training period required for users to become proficient. Overall, hybrid BCI-spellers have the potential to improve communication for individuals with impairments by combining the strengths of multiple types of BCI-spellers. In conclusion, BCI-spellers are a promising technology for individuals with communication impairments. P300, MI, and SSVEP are the three main types of BCI-spellers, each with their own advantages and limitations. Further research is needed to improve the accuracy and usability of BCI-spellers and to explore their potential applications in other areas such as gaming and virtual reality.

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          Most cited references38

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          Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

          This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., 'locked-in' patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min.
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            Brain-computer interfaces for communication and control.

            For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world - a brain-computer interface (BCI). Over the past 15 years, productive BCI research programs have arisen. Encouraged by new understanding of brain function, by the advent of powerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programs concentrate on developing new augmentative communication and control technology for those with severe neuromuscular disorders, such as amyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury. The immediate goal is to provide these users, who may be completely paralyzed, or 'locked in', with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses. Present-day BCIs determine the intent of the user from a variety of different electrophysiological signals. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. They are translated in real-time into commands that operate a computer display or other device. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance. Current BCIs have maximum information transfer rates up to 10-25bits/min. This limited capacity can be valuable for people whose severe disabilities prevent them from using conventional augmentative communication methods. At the same time, many possible applications of BCI technology, such as neuroprosthesis control, may require higher information transfer rates. Future progress will depend on: recognition that BCI research and development is an interdisciplinary problem, involving neurobiology, psychology, engineering, mathematics, and computer science; identification of those signals, whether evoked potentials, spontaneous rhythms, or neuronal firing rates, that users are best able to control independent of activity in conventional motor output pathways; development of training methods for helping users to gain and maintain that control; delineation of the best algorithms for translating these signals into device commands; attention to the identification and elimination of artifacts such as electromyographic and electro-oculographic activity; adoption of precise and objective procedures for evaluating BCI performance; recognition of the need for long-term as well as short-term assessment of BCI performance; identification of appropriate BCI applications and appropriate matching of applications and users; and attention to factors that affect user acceptance of augmentative technology, including ease of use, cosmesis, and provision of those communication and control capacities that are most important to the user. Development of BCI technology will also benefit from greater emphasis on peer-reviewed research publications and avoidance of the hyperbolic and often misleading media attention that tends to generate unrealistic expectations in the public and skepticism in other researchers. With adequate recognition and effective engagement of all these issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
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              Brain–Computer Interface Spellers: A Review

              A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                23 August 2023
                2023
                : 17
                : 1216648
                Affiliations
                [1] 1Neurosciences Research Institute, Samara State Medical University , Samara, Russia
                [2] 2Baltic Center for Neurotechnologies and Artificial Intelligence, Immanuel Kant Baltic Federal University , Kaliningrad, Russia
                [3] 3Department of Operative Surgery and Clinical Anatomy with a Course of Innovative Technologies, Samara State Medical University , Samara, Russia
                [4] 4Department of Physical Culture, I.M. Sechenov First Moscow State Medical University (Sechenov University) , Moscow, Russia
                Author notes

                Edited by: Jiahui Pan, South China Normal University, China

                Reviewed by: Reza Abiri, University of Rhode Island, United States

                *Correspondence: Alexander Zakharov, a.v.zaharov@ 123456samsmu.ru
                Article
                10.3389/fnhum.2023.1216648
                10480564
                37680264
                1b4109a5-0567-40b2-80b3-01d98c52fb40
                Copyright © 2023 Maslova, Komarova, Shusharina, Kolsanov, Zakharov, Garina and Pyatin.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 May 2023
                : 24 July 2023
                Page count
                Figures: 12, Tables: 1, Equations: 0, References: 38, Pages: 10, Words: 6070
                Categories
                Neuroscience
                Mini Review
                Custom metadata
                Brain-Computer Interfaces

                Neurosciences
                brain-computer interface,people with disabilities,motor imagery,p300,speller
                Neurosciences
                brain-computer interface, people with disabilities, motor imagery, p300, speller

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