TY - GEN
T1 - Motor intention recognition in EEG
T2 - 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
AU - Iturralde, Pablo A.
AU - Patrone, Martín
AU - Lecumberry, Federico
AU - Fernández, Alicia
PY - 2012
Y1 - 2012
N2 - Brain-computer interfaces (BCIs) based on electroencephalograms (EEG) are a noninvasive and cheap alternative to get a communication channel between brain and computers. Some of the main issues with EEG signals are its high dimensionality, high inter-user variance, and non-stationarity. In this work we present different approaches to deal with the high dimensionality of the data, finding relevant descriptors in EEG signals for motor intention recognition: first, a classical dimensionality reduction method using Diffusion Distance, second a technique based on spectral analysis of EEG channels associated with the frontal and prefrontal cortex, and third a projection over average signals. Performance analysis for different sets of features is done, showing that some of them are more robust to user variability.
AB - Brain-computer interfaces (BCIs) based on electroencephalograms (EEG) are a noninvasive and cheap alternative to get a communication channel between brain and computers. Some of the main issues with EEG signals are its high dimensionality, high inter-user variance, and non-stationarity. In this work we present different approaches to deal with the high dimensionality of the data, finding relevant descriptors in EEG signals for motor intention recognition: first, a classical dimensionality reduction method using Diffusion Distance, second a technique based on spectral analysis of EEG channels associated with the frontal and prefrontal cortex, and third a projection over average signals. Performance analysis for different sets of features is done, showing that some of them are more robust to user variability.
UR - http://www.scopus.com/inward/record.url?scp=84865612776&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33275-3_68
DO - 10.1007/978-3-642-33275-3_68
M3 - Contribución a la conferencia
AN - SCOPUS:84865612776
SN - 9783642332746
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 551
EP - 558
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
Y2 - 3 September 2012 through 6 September 2012
ER -