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Neurofeedback games using EEG-based brain–computer interface technology

Neurofeedback games using EEG-based brain–computer interface technology

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Brain-computer interface (BCI) is relatively a new approach to communication between man and machine, which translates brain activity into commands for communication and control. As BCI is capable of detecting human intentions, it is a promising communication tool for paralyzed patients for communicating with external world. Many of the current BCI systems employ electroencephalogram (EEG) which is the most widely used noninvasive brain activity recording technique. EEG signal carries potential features to identify and decode human intentions and mental tasks. Recently, many researchers have started exploiting the possibilities of BCI in entertainment and cognitive skill enhancement. BCI-based games have been identified as a unique entertainment mechanism nowadays, “controlling a 2-D, 3-D or virtual computer game solely by player's brain waves.” BCI games work based on a neurofeedback paradigm which allows an individual to self-regulate his brain signal in response to the real-time visual or auditory feedback of his brain waves/features. This neurofeedback in a gaming environment motivates and trains the players to control his brain features toward the desired stage (self-regulation). This chapter explores the state-of-the-art BCI technology in neurofeedback games, employing EEG signal. It also provides a survey of the existing EEG-based neurofeedback games and evaluates their success rates, challenging factors and influence on players. In neurofeedback games, a number of features extracted from EEG accompanied with sustained attention, selective attention, visuospatial attention, motor imagery, eye movements, etc. have been employed as distinct control signals. We will briefly review and compare various signal processing methodologies and machine-learning techniques employed in those studies to extract and decode the brain features. Besides the structure and algorithms used in neurofeedback games, the therapeutic effects of neurofeedback training and its capabilities for the enhancement of cognitive skills will also be briefly discussed in this chapter. Neurofeedback training helps to rewire brain's underlying neural circuits and to improve brain functions. Therefore, it is considered as an effective tool for boosting cognitive skills of both healthy and the disabled. Specifically, neurofeedback has been considered as an efficient treatment modality for individuals with attention-deficit hyperactive disorder (ADHD). ADHD is characterized by three behavioral symptoms: inattention, hyperactivity and impulsivity. Along with the conventional intervention strategies such as medication, behavioral treatments, etc., neurofeedback in BCI games has also been emerging as a promising modality for treating the attention deficit. We will also discuss portable and economical EEG recording devices currently employed in BCI-based brain training modules/games. Finally, the chapter will be concluded with a brief overview of the neurofeedback developments in the context of BCI-based games until now, their potential impact on the healthy as well as on people with neurological disorders, challenges in transferring the successful protocols from laboratories into the market and hurdles in real-time BCI system design and development.

Chapter Contents:

  • Abstract
  • 14.1 Introduction
  • 14.2 Generic framework of a neurofeedback game using BCI technology
  • 14.2.1 Data acquisition
  • 14.2.2 Data processing
  • 14.2.3 Control signal generation
  • 14.2.4 Gaming interface
  • 14.3 Classification of neurofeedback games based on BCI interaction
  • 14.3.1 Active BCI games
  • 14.3.1.1 Shooter game
  • 14.3.1.2 Pacman game
  • 14.3.1.3 World of Warcraft
  • 14.3.1.4 Pinball game
  • 14.3.1.5 Brain arena: a football game
  • 14.3.1.6 Brain runner
  • 14.3.1.7 Spaceship game
  • 14.3.1.8 Car racing game
  • 14.3.2 Reactive BCI games
  • 14.3.2.1 Mind balance game
  • 14.3.2.2 Car racing game
  • 14.3.2.3 Tower protection game
  • 14.3.2.4 Spacecraft game
  • 14.3.2.5 Virtual claw game
  • 14.3.2.6 Checker game
  • 14.3.2.7 Memory game
  • 14.3.2.8 Game with virtual class room
  • 14.3.2.9 Space Invaders
  • 14.3.3 Passive BCI games
  • 14.3.3.1 Brain ball
  • 14.3.3.2 Fruit picking game
  • 14.3.3.3 Mind-Ninja
  • 14.3.3.4 Drawing game
  • 14.3.3.5 Harvest challenge
  • 14.3.3.6 Shooting game
  • 14.3.3.7 Brain Cogo-Land
  • 14.3.3.8 Ball game
  • 14.3.3.9 Multiplayer monster game
  • 14.3.3.10 Matrix game
  • 14.3.4 Hybrid games
  • 14.4 EEG devices for neurofeedback development
  • 14.5 Benefits of neurofeedback games
  • 14.5.1 Novel entertainment modality
  • 14.5.2 Cognitive enhancement tool in the neurologically challenged as well as healthy
  • 14.5.3 BCI performance booster
  • 14.6 Challenges in practical implementation
  • 14.7 Conclusion
  • References

Inspec keywords: feedback; neurophysiology; feature extraction; electroencephalography; medical disorders; learning (artificial intelligence); medical signal processing; brain-computer interfaces; computer games

Other keywords: ADHD; EEG signal; BCI systems; electroencephalogram; EEG-based brain-computer interface technology; brain activity; neurofeedback developments; neurological disorders; attention-deficit hyperactive disorder; EEG-based neurofeedback games; neurofeedback paradigm; BCI games; neurofeedback training; feature extraction; brain signal; BCI technology; cognitive skill enhancement; gaming environment; machine-learning techniques; brain functions; BCI-based brain training modules; signal processing methodologies; virtual computer game

Subjects: Digital signal processing; Bioelectric signals; Electrical activity in neurophysiological processes; Electrodiagnostics and other electrical measurement techniques; Computer games; User interfaces; Knowledge engineering techniques; Signal processing and detection; Biology and medical computing

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