Data from: Optimizing the detection of wakeful and sleep-like states for future electrocorticographic brain computer interface applications

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关键词：

Sleep;Brain Computer Interfaces;Human Cortex;Machine Learning;Electrocorticography

DOI：

doi:10.5061/dryad.4f92n

摘要：

Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Tra

Data from: Adaptive multi-degree of freedom Brain Computer Interface using online feedback: Towards novel methods and metrics of mutual adaptation

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关键词：

brain machine interface

DOI：

doi:10.5061/dryad.609g597

摘要：

This paper proposes a novel adaptive online-feedback methodology for Brain Computer Interfaces (BCI). The method uses ElectroEncephaloGraphic (EEG

Data from: I meant to do that: determining the intentions of action in the face of disturbances

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关键词：

human;Feedback;feedforward;control of movement;Prediction;internal model;generative model;arm reaching;error;upper extremity;intention

DOI：

doi:10.5061/dryad.1257p

摘要：

-time determination (and manipulation) of error in training, and complex systems that embody planning such as brain machine interfaces, te

Data from: Classifying three imaginary states of the same upper extremity using time-domain features

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DOI：

doi:10.5061/dryad.6qs86

摘要：

Brain-computer interface (BCI) allows collaboration between humans and machines. It translates the electrical activity of the brain to under