A self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms
Movement execution results in the simultaneous generation of movement-related potentials (MRP) as well as changes in the power of Mu and Beta rhythms. This paper proposes a new self-paced multi-channel BI that combines features extracted from MRPs and from changes in the power of Mu and Beta rhythms...
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| Veröffentlicht in: | Journal of computational neuroscience 2007-08, Vol.23 (1), p.21-37 |
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| container_title | Journal of computational neuroscience |
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| creator | Fatourechi, Mehrdad Birch, Gary E Ward, Rabab K |
| description | Movement execution results in the simultaneous generation of movement-related potentials (MRP) as well as changes in the power of Mu and Beta rhythms. This paper proposes a new self-paced multi-channel BI that combines features extracted from MRPs and from changes in the power of Mu and Beta rhythms. We developed a new algorithm to classify the high-dimensional feature space. It uses a two-stage multiple-classifier system (MCS). First, an MCS classifies each neurological phenomenon separately using the information extracted from specific EEG channels (EEG channels are selected by a genetic algorithm). In the second stage, another MCS combines the outputs of MCSs developed in the first stage. Analysis of the data of four able-bodied subjects shows the superior performance of the proposed algorithm compared with a scheme where the features were all combined in a single feature vector and then classified. |
| doi_str_mv | 10.1007/s10827-006-0017-3 |
| format | Article |
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| subjects | Brain - physiology Electroencephalography Evoked Potentials, Visual - physiology Humans Movement - physiology Periodicity Photic Stimulation - methods Psychomotor Performance - physiology Time Perception - physiology User-Computer Interface |
| title | A self-paced brain interface system that uses movement related potentials and changes in the power of brain rhythms |
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