Endogenous brain-machine interface based on the correlation of EEG maps
作者： Andrés Úbeda , Eduardo Iáñez , José M. Azorín , Carlos Perez-Vidal
DOI: 10.1016/J.CMPB.2013.01.012
关键词:
摘要: In this paper, a non-invasive endogenous brain-machine interface (BMI) based on the correlation of EEG maps has been developed to work in real-time applications. The classifier is able detect two mental tasks related motor imagery with good success rates and stability. BMI tested four able-bodied volunteers. First, users performed training visual feedback adjust classifier. Afterwards, carried out several trajectories controlling cursor position BMI. these tests, score accuracy were measured. results showed that participants follow targets during trajectory, proving mapping ready more complex applications aimed at helping people severe disability their daily life.
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