BCI-Based Navigation in Virtual and Real Environments

A Brain-Computer Interface (BCI) is a system that enables people to control an external device with their brain activity, without the need of any muscular activity. Researchers in the BCI field aim to develop applications to improve the quality of life of severely disabled patients, for whom a BCI can be a useful channel for interaction with their environment. Some of these systems are intended to control a mobile device (e. g. a wheelchair). Virtual Reality is a powerful tool that can provide the subjects with an opportunity to train and to test different applications in a safe environment. This technical review will focus on systems aimed at navigation, both in virtual and real environments.This work was partially supported by the Innovation, Science and Enterprise Council of the Junta de Andalucía (Spain), project P07-TIC-03310, the Spanish Ministry of Science and Innovation, project TEC 2011-26395 and by the European fund ERDF

Games and Brain-Computer Interfaces: The State of the Art

BCI gaming is a very young field; most games are proof-of-concepts. Work that compares BCIs in a game environments with traditional BCIs indicates no negative effects, or even a positive effect of the rich visual environments on the performance. The low transfer-rate of current games poses a problem for control of a game. This is often solved by changing the goal of the game. Multi-modal input with BCI forms an promising solution, as does assigning more meaningful functionality to BCI control

A Dual-Channel Optical Brain-Computer Interface In A Gaming Environment

This paper explores the viability of using a novel optical Brain-Computer Interface within a gaming environment. We describe a system that incorporates a 3D gaming engine and an optical BCI. This made it possible to classify activation in the motor cortex within a synchronous experimental paradigm. Detected activations were used to control the arm movement of a human model in the graphical engine

A Dual-Channel Optical Brain-Computer Interface In A Gaming Environment

This paper explores the viability of using a novel optical Brain-Computer Interface within a gaming environment. We describe a system that incorporates a 3D gaming engine and an optical BCI. This made it possible to classify activation in the motor cortex within a synchronous experimental paradigm. Detected activations were used to control the arm movement of a human model in the graphical engine

Improving the Brain-Computer Interface Learning Process with Gamification in Motor Imagery: A Review

Brain-computer-interface-based motor imagery (MI-BCI), a control method for transferring the imagination of motor behavior to computer-based commands, could positively impact neural functions. With the safety guaranteed by non-invasive BCI devices, this method has the potential to enhance rehabilitation and physical outcomes. Therefore, this MI-BCI control strategy has been highly researched. However, applying a non-invasive MI-BCI to real life is still not ideal. One of the main reasons is the monotonous training procedure. Although researchers have reviewed optimized signal processing methods, no suggestion is found in training feedback design. The authors believe that enhancing the engagement interface via gamification presents a potential method that could increase the MI-BCI outcome. After analyzing 2524 articles (from 2001 to 2020), 28 pieces of research are finally used to evaluate the feasibility of using gamified MI-BCI system for training. This paper claims that gamification is feasible for MI-BCI training with an average accuracy of 74.35% among 111 individuals and positive reports from 26 out of 28 studies. Furthermore, this literature review suggests more emphasis should be on immersive and humanoid design for a gaming system, which could support relieving distraction, stimulate correct MI and improve learning outcomes. Interruptive training issues such as disturbing graphical interface design and potential solutions have also been presented for further research

Hybrid BCI Coupling EEG and EMG for Severe Motor Disabilities

AbstractIn this paper, we are studying hybrid Brain-Computer Interfaces (BCI) coupling joystick data, electroencephalogram (EEG – electrical activity of the brain) and electromyogram (EMG – electrical activity of muscles) activities for severe motor disabilities. We are focusing our study on muscular activity as a control modality to interact with an application. We present our data processing and classification technique to detect right and left hand movements. EMG modality is well adapted for DMD patients, because less strength is needed to detect movements in contrast to conventional interfaces like joysticks. Across virtual reality tools, we believe that users will be more able to understand how to interact with such kind of interactive systems. This first part of our study report some very good results concerning the detection of hand movements, according to muscular channel, on healthy subjects