scholarly journals Concept, development and evaluation of a mind action game with the electro encephalograms as an auxiliary input

2017 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Mark Joselli ◽  
Fabio Binder ◽  
Esteban Clua ◽  
Eduardo Soluri
Keyword(s):  
Concept Development ◽  
Computer Interface ◽  
Proof Of Concept ◽  
New Paradigm ◽  
Input Devices ◽  
Interactive Applications ◽  
Touch Input ◽  
Attention Level ◽  
The Brain ◽  
Auxiliary Input

Games are interactive applications that require input devices in order to send messages for the interaction. Normally this input devices are mouse, keyboards and joysticks. Lately, this input has been done in different ways, such as voice, touch and movement with new input devices. One type of input that has not been very explored is the use of the brain waves as a input for the game. While in past these devices where expensive, nowadays Brain Computer Interface (BCI) have become accessible, cheap and can be acquired with nonintrusive top off-the-shelf products, which can create a new paradigm of interaction for games. This work presents a novel architecture and framework that can help the development of games with both BCI and traditional interfaces. As a proof of concept, this paper shows the experience in designing and developing a game prototype using the framework and EEG brainwaves as one of the players input. The game is an action slice game, similar to Fruit Ninja, called MindNinja. This game differ form most BCI game, since it is based on an action game, using touch input where the BCI is used as an auxiliary input to change the game behavior. This game was tested and evaluated with a group of person, showing promising results in the fun level, as well as increasing the attention level of subjects.

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

scholarly journals Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA

Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 647 ◽  
Author(s):  
Carlos Pérez Díaz ◽  
Jonathan Muñoz ◽  
Tarendra Lakhankar ◽  
Reza Khanbilvardi ◽  
Peter Romanov
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Concept Development ◽  
Proof Of Concept

Classification of EEG Mental Patterns by Using Two Scalp Electrodes and Mahalanobis Distance-Based Classifiers

2002 ◽  
Vol 41 (04) ◽  
pp. 337-341 ◽  
Author(s):  
F. Cincotti ◽  
D. Mattia ◽  
C. Babiloni ◽  
F. Carducci ◽  
L. Bianchi ◽  
...  
Keyword(s):  
Mahalanobis Distance ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Correct Classification ◽  
Interface Area ◽  
System A ◽  
The Brain ◽  
Full Covariance Matrix ◽  
Recording Electrodes

Summary Objectives: In this paper, we explored the use of quadratic classifiers based on Mahalanobis distance to detect mental EEG patterns from a reduced set of scalp recording electrodes. Methods: Electrodes are placed in scalp centro-parietal zones (C3, P3, C4 and P4 positions of the international 10-20 system). A Mahalanobis distance classifier based on the use of full covariance matrix was used. Results: The quadratic classifier was able to detect EEG activity related to imagination of movement with an affordable accuracy (97% correct classification, on average) by using only C3 and C4 electrodes. Conclusions: Such a result is interesting for the use of Mahalanobis-based classifiers in the brain computer interface area.

Normal saline as a natural intravascular contrast agent for dynamic perfusion-weighted MRI of the brain: Proof of concept at 1.5T

2016 ◽  
Vol 44 (6) ◽  
pp. 1580-1591 ◽  
Author(s):  
Hernán Jara ◽  
Asim Mian ◽  
Osamu Sakai ◽  
Stephan W. Anderson ◽  
Mitchel J. Horn ◽  
...  
Keyword(s):  
Contrast Agent ◽  
Normal Saline ◽  
Proof Of Concept ◽  
Intravascular Contrast Agent ◽  
The Brain

Research of “Yes” and “No” Responses by Auditory Stimuli in Human EEG

2013 ◽  
Vol 310 ◽  
pp. 660-664 ◽  
Author(s):  
Zi Guang Li ◽  
Guo Zhong Liu
Keyword(s):  
Communication Channel ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Auditory Stimuli ◽  
Support Vector ◽  
Quality Life ◽  
Asking Questions ◽  
Command Signals ◽  
Different Characteristics ◽  
The Brain

As an emerging technology, brain-computer interface (BCI) bring us a novel communication channel which translate brain activities into command signals for devices like computer, prosthesis, robots, and so forth. The aim of the brain-computer interface research is to improve the quality life of patients who are suffering from server neuromuscular disease. This paper focus on analyzing the different characteristics of the brainwaves when a subject responses “yes” or “no” to auditory stimulation questions. The experiment using auditory stimuli of form of asking questions is adopted. The extraction of the feature adopted the method of common spatial patterns(CSP) and the classification used support vector machine (SVM) . The classification accuracy of "yes" and "no" answers achieves 80.2%. The experiment result shows the feasibility and effectiveness of this solution and provides a basis for advanced research .

scholarly journals A comparative study: use of a Brain-computer Interface (BCI) device by people with cerebral palsy in interaction with computers

2015 ◽  
Vol 87 (4) ◽  
pp. 1929-1937 ◽  
Author(s):  
Regina O. Heidrich ◽  
Emely Jensen ◽  
Francisco Rebelo ◽  
Tiago Oliveira
Keyword(s):  
Cerebral Palsy ◽  
Comparative Study ◽  
Case Studies ◽  
Brain Computer Interface ◽  
Product Evaluation ◽  
Computer Interface ◽  
Healthy Controls ◽  
The Brain

ABSTRACT This article presents a comparative study among people with cerebral palsy and healthy controls, of various ages, using a Brain-computer Interface (BCI) device. The research is qualitative in its approach. Researchers worked with Observational Case Studies. People with cerebral palsy and healthy controls were evaluated in Portugal and in Brazil. The study aimed to develop a study for product evaluation in order to perceive whether people with cerebral palsy could interact with the computer and compare whether their performance is similar to that of healthy controls when using the Brain-computer Interface. Ultimately, it was found that there are no significant differences between people with cerebral palsy in the two countries, as well as between populations without cerebral palsy (healthy controls).

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