In this study we summarize the features that characterize the pre-movements and pre-motor imageries (before imagining the movement) electroencephalography (EEG) data in humans from both Neuroscientists' and Engineers' point of view. We demonstrate what the brain status is before a voluntary movement and how it has been used in practical applications such as brain computer interfaces (BCIs). Usually, in BCI applications, the focus of study is on the after-movement or motor imagery potentials. However, this study shows that it is possible to develop BCIs based on the before-movement or motor imagery potentials such as the Bereitschaftspotential (BP). Using the pre-movement or pre-motor imagery potentials, we can correctly predict the onset of the upcoming movement, its direction and even the limb that is engaged in the performance. This information can help in designing a more efficient rehabilitation tool as well as BCIs with a shorter response time which appear more natural to the users.

How capable is non-invasive EEG data of predicting the next movement? A mini review / Pouya, Ahmadian; Cagnoni, Stefano; Ascari, Luca. - In: FRONTIERS IN HUMAN NEUROSCIENCE. - ISSN 1662-5161. - 7:124(2013), pp. 1-7. [10.3389/fnhum.2013.00124]

How capable is non-invasive EEG data of predicting the next movement? A mini review

CAGNONI, Stefano;ASCARI, Luca
2013-01-01

Abstract

In this study we summarize the features that characterize the pre-movements and pre-motor imageries (before imagining the movement) electroencephalography (EEG) data in humans from both Neuroscientists' and Engineers' point of view. We demonstrate what the brain status is before a voluntary movement and how it has been used in practical applications such as brain computer interfaces (BCIs). Usually, in BCI applications, the focus of study is on the after-movement or motor imagery potentials. However, this study shows that it is possible to develop BCIs based on the before-movement or motor imagery potentials such as the Bereitschaftspotential (BP). Using the pre-movement or pre-motor imagery potentials, we can correctly predict the onset of the upcoming movement, its direction and even the limb that is engaged in the performance. This information can help in designing a more efficient rehabilitation tool as well as BCIs with a shorter response time which appear more natural to the users.
2013
How capable is non-invasive EEG data of predicting the next movement? A mini review / Pouya, Ahmadian; Cagnoni, Stefano; Ascari, Luca. - In: FRONTIERS IN HUMAN NEUROSCIENCE. - ISSN 1662-5161. - 7:124(2013), pp. 1-7. [10.3389/fnhum.2013.00124]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2616647
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