Novel hybrid brain–computer interface system based on motor imagery and P300
نویسندگان
چکیده
منابع مشابه
A Study of Various Feature Extraction Methods on a Motor Imagery Based Brain Computer Interface System
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...
متن کاملa study of various feature extraction methods on a motor imagery based brain computer interface system
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) classifier...
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Directly from the brain thinking activity signals to communicate with the outside world, to achieve the heart and heart communication, achieve control of the surrounding environment, even is the dream of human beings since the ancient times is the pursuit of. Brain-computer Interface (Brian Computer Interface: BCI) this novel human-computer interaction mode provides the scientific way to realiz...
متن کاملRemoving Unrelated Features Based on Linear Dynamical System for Motor-Imagery-Based Brain-Computer Interface
Common spatial pattern (CSP) is very successful in constructing spatial filters for detecting event-related synchronization and event-related desynchronization. In statistics, a CSP filter can optimally separate the motor-imagery-related components. However, for a single trail, the EEG features extracted after a CSP filter still include features not related to motor imagery. In this study, we i...
متن کاملAn Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300
The hybrid brain computer interface (BCI) based on motor imagery (MI) and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together b...
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ژورنال
عنوان ژورنال: Cognitive Neurodynamics
سال: 2019
ISSN: 1871-4080,1871-4099
DOI: 10.1007/s11571-019-09560-x