A group of Spanish researchers have developed a brain-computer interface based on electroencephalograms that allowed a group of 22 users to play a simple multiplayer game. The interface was 94% accurate in translating players’ thoughts into game moves, with each move taking just over 5 seconds. The study was published in Frontiers in Human Neuroscience.
A brain-computer interface is a technology that enables direct communication between the human brain and external devices, such as computers or prosthetic limbs. Brain-computer interfaces work by detecting and interpreting neural signals, typically through electrodes placed on the user’s head. These signals are then translated into actionable commands, allowing individuals to control computers, devices, or applications using their thoughts.
Brain-computer interfaces offer significant potential in medicine, from helping paralyzed individuals regain environmental control to treating neurological disorders. However, their broader adoption is hindered by challenges in accuracy and the extended time required to interpret brain signals.
One promising approach to developing better performing brain-computer interfaces is the use of code-modulated visual evoked potentials. Code-modulated visual evoked potentials (c-VEPs) are a type of brain-computer interface technology that utilizes visual stimuli with specific codes to elicit distinct neural responses in the brain.
Study author Selene Moreno-Calderón and her colleagues wanted to design, develop and evaluate a multiplayer video game that would be using c-VEPs, a game that players would be able to play, and play effectively, solely using their thoughts. They crafted a rendition of the “Connect 4” game, a two-player strategy contest where participants alternate dropping colored discs into a vertical grid, aiming to be the first to align four discs either horizontally, vertically, or diagonally.
The study involved 22 healthy participants who undertook three different game variants in one session. Participants had an average age of 28, with 10 being female. Among them, six had prior experience with brain-computer interface systems.
The brain-computer interface used to translate neural signals of players into game moves used electroencephalographic signals as input. The researchers placed eight electrodes on the head of each participant at different points and used Bluetooth to connect the EEG system to the computer running the game. They needed a bit less than a minute to calibrate the system for a specific user.
Results showed that the accuracy of converting participants’ intentions into game actions ranged between 91% and 95%, with an overall average of 94% across all tasks. The system executed about 11 moves per minute, translating to slightly more than 5 seconds per action. Participants expressed satisfaction with the game, praising its intuitiveness, ease of learning, and fluid responsiveness.
“This study focused on designing, developing and evaluating a version of the popular multiplayer game “Connect 4” with a brain-computer interface system based on c-VEP. The application was evaluated on 22 healthy users, obtaining promising results. An average accuracy of 93.74% ± 1.71% was achieved, suggesting that the use of c-VEPs is appropriate for developing a multiplayer competitive video game,” the study authors concluded.
The study makes an important contribution to the exploration of brain-computer interface uses. However, while brain-computer interfaces and the ability to control games using thoughts can certainly be considered revolutionary, compared to most video games the game used in the study can be considered relatively slow-paced and simple. Additionally, for widespread application of such control systems in the entertainment industry, electrodes that require putting gel on users’ heads will likely not do. They will have to be replaced with something more comfortable.
The paper, “Combining brain-computer interfaces and multiplayer video games: an application based on c-VEPs”, was authored by Selene Moreno-Calderón, Víctor Martínez-Cagigal, Eduardo Santamaría-Vázquez, Sergio Pérez-Velasco, Diego Marcos-Martínez, and Roberto Hornero.
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