Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links bet...

Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field. Nonetheless, it is also worth mentioning that with these improvements, new challenges are constantly discovered. This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given. Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics. Finally, the challenges to the recent BCI systems are discussed, and possible solutions to mitigate the issues are recommended.

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Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

OBJECTIVE Since the mid-1990s, a significant scientific literature has evolved regarding the outcomes from the use of what we now refer to as clinical virtual reality (VR) This use of VR simulation technology has produced encouraging results when applied to address cognitive, psychological, motor, and functional impairments across a wide range of clinical health conditions This article addresses the question, "Is clinical VR ready for primetime?" METHOD After a brief description of the various forms of VR technology, we discuss the trajectory of clinical VR over the last 20 years and summarize the basic assets that VR offers for creating clinical applications The discussion then addresses the question of readiness in terms of the theoretical basis for clinical VR assets, the research to date, the pragmatic factors regarding availability, usability, and costs of clinical VR content/systems, and the ethical issues for the safe use of VR with clinical populations RESULTS Our review of the theoretical underpinnings and research findings to date leads to the prediction that clinical VR will have a significant impact on future research and practice Pragmatic issues that can influence adoption across many areas of psychology also appear favorable, but professional guidelines will be needed to promote its safe and ethical use CONCLUSIONS Although there is still much research needed to advance the science in this area, we strongly believe that clinical VR applications will become indispensable tools in the toolbox of psychological researchers and practitioners and will only grow in relevance and popularity in the future (PsycINFO Database Record

Is clinical virtual reality ready for primetime

This paper presents a systematic review of electroencephalography (EEG)-based brain---computer interfaces (BCIs) used in the video games, a vibrant field of research that touches upon all relevant questions concerning the future directions of BCI. The paper examines the progress of BCI research with regard to games and shows that gaming applications offer numerous advantages by orienting BCI to concerns and expectations of a gaming application. Different BCI paradigms are investigated, and future directions are discussed.

EEG-based BCI and video games: a progress report

In recent years, research on Brain-Computer Interface (BCI) technology for healthy users has attracted considerable interest, and BCI games are especially popular. This study reviews the current status of, and describes future directions, in the field of BCI games. To this end, we conducted a literature search and found that BCI control paradigms using electroencephalographic signals (motor imagery, P300, steady state visual evoked potential and passive approach reading mental state) have been the primary focus of research. We also conducted a survey of nearly three hundred participants that included researchers, game developers and users around the world. From this survey, we found that all three groups (researchers, developers and users) agreed on the significant influence and applicability of BCI and BCI games, and they all selected prostheses, rehabilitation and games as the most promising BCI applications. User and developer groups tended to give low priority to passive BCI and the whole head sensor array. Developers gave higher priorities to “the easiness of playing” and the “development platform” as important elements for BCI games and the market. Based on our assessment, we discuss the critical point at which BCI games will be able to progress from their current stage to widespread marketing to consumers. In conclusion, we propose three critical elements important for expansion of the BCI game market: standards, gameplay and appropriate integration.

/pdf/a-review-of-brain-computer-interface-games-and-an-opinion-1evd2tirli.pdf

A Review of Brain-Computer Interface Games and an Opinion Survey from Researchers, Developers and Users

The P300-based brain-computer interface (P300 BCI) is currently a very popular topic in assistive technology development. However, only a few simple P300 BCI-based games have been designed so far. Here, we analyze the shortcomings of this BCI in gaming applications and show that solutions for overcoming them already exist, although these techniques are dispersed over several different games. Additionally, new approaches to improve the P300 BCI accuracy and flexibility are currently being proposed in the more general P300 BCI research. The P300 BCI, even in its current form, not only exhibits relatively high speed and accuracy, but also can be used without user training, after a short calibration. Taking these facts together, the broader use of the P300 BCI in BCI-controlled video games is recommended.

Adapting the P300-Based Brain–Computer Interface for Gaming: A Review

We put forward the hypothesis that the amplitudes of the P300 and N200 components of visual potentials evoked by flashes of the columns and rows of symbols in a matrix depend on the nature of the task attracting the operator’s attention to target symbol stimuli: 1) simple observation of the flashes of the target symbol; 2) observation with counting the numbers of these flashes and monitoring the success of this operation; 3) observation of the flashes of the target symbol with display of the symbol on a screen when the subject’s attention to this symbol was detected using the EEG as a brain–computer interface. Studies using a group of 17 subjects showed that the maximum amplitudes of the P300 and N200 components of visual potentials were reached to a statistically significant level in the second operator attention regime, which did not require involvement in a brain–computer interface. The second condition showed the largest number of statistically significant differences between the amplitudes of the P300 and N200 components of visual potentials evoked by flashes of target and nontarget symbols. At the same time, the smallest amplitudes of these components and the smallest differences between reactions to the target and nontarget stimuli were seen in conditions of simple observation of the flashes of the target stimuli. These results lead to the conclusion that successful operator functioning in a brain–computer interface does not require the maximal expression of the P300 and N200 components of visual potentials, which probably start to be optimized in the brain–computer interface in the task of controlling external processes, such as display of the target symbol on the computer screen.

http://brain.bio.msu.ru/papers/Basyul_Kaplan_2015_Changes_in_the_N200_and_P300_Components_of_ERPs_on_Variations_in_the_Conditions_of_Attention_in_a_BCI.pdf

Changes in the N200 and P300 Components of Event-Related Potentials on Variations in the Conditions of Attention in a Brain-Computer Interface System

http://brain.bio.msu.ru/papers/Basyul_Kaplan_2014_ZhVND_N200_and_P300_dependence_on_attention_variations_in_P300_BCI.pdf

I. A. Basyul

Papers

Adapting the P300-Based Brain–Computer Interface for Gaming: A Review

Changes in the N200 and P300 Components of Event-Related Potentials on Variations in the Conditions of Attention in a Brain-Computer Interface System

Изменения n200 и p300 компонентов потенциалов, связанных с событиями, при варьировании условий внимания в системе brain computer interface