An Effective Brain-Computer Interface System Based on the Optimal Timeframe Selection of Brain Signals
نویسندگان
چکیده
منابع مشابه
Development of a Brain Computer Interface (BCI) Speller System Based on SSVEP Signals
BCI is one of the most intriguing technologies among other HCI systems, mostly because of its capability of recording brain activities. Spelling BCIs, which help paralyzed people to maintain communication, are one of the striking topics in the field of BCI. In this scientific a spelling BCI system with high transfer rate and accuracy that uses SSVEP signals is proposed.In addition, we suggested...
متن کاملdevelopment of a brain computer interface (bci) speller system based on ssvep signals
bci is one of the most intriguing technologies among other hci systems, mostly because of its capability of recording brain activities. spelling bcis, which help paralyzed people to maintain communication, are one of the striking topics in the field of bci. in this scientific a spelling bci system with high transfer rate and accuracy that uses ssvep signals is proposed. in addition, we suggeste...
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Introduction: Brain Computer Interface (BCI) systems based on Movement Imagination (MI) are widely used in recent decades. Separate feature extraction methods are employed in the MI data sets and classified in Virtual Reality (VR) environments for real-time applications. Methods: This study applied wide variety of features on the recorded data using Linear Discriminant Analysis (LDA) classifie...
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User interfaces are always one of the most important applied and study fields of information technology. The development and expansion of cognitive science studies and functionalization of its tools such as BCI1, as well as popularization of methods such as SSVEP2 to stimulate brain waves, have led to using these techniques every day, especially in appropriate solutions for physically and menta...
متن کاملOptimal Parameterization Selection for the Brain-Computer Interface
The contribution deals with the optimization of the EEG off-line, single-trial movement classification by means of parameterization tuning. The data we classify represent manifestations of the simple movements performed by the right shoulder (proximal movement) and right index finger (distal movement) of experimental subjects. We implemented several approaches to the EEG parameterization and co...
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ژورنال
عنوان ژورنال: International Clinical Neuroscience Journal
سال: 2018
ISSN: 2383-1871,2383-2096
DOI: 10.15171/icnj.2018.07