RT Book, Section
T1 Chapter 8 Neurofeedback and Brain-Computer Interface. Clinical Applications
A1 Birbaumer, Niels
A1 Ramos Murguialday, Ander
A1 Weber, Cornelia
A1 Montoya, Pedro
A2 Rossini, Luca
A2 Izzo, Dario
A2 Summerer, Leopold
AB Most of the research devoted to BMI development consists of methodological studies comparing different online mathematical algorithms, ranging from simple linear discriminant analysis (LDA) (Dornhege et al., 2007) to nonlinear artificial neural networks (ANNs) or support vector machine (SVM) classification. Single cell spiking for the reconstruction of hand movements requires different statistical solutions than electroencephalography (EEG)-rhythm classification for communication. In general, the algorithm for BMI applications is computationally simple and differences in classification accuracy between algorithms used for a particular purpose are small. Only a very limited number of clinical studies with neurological patients are available, most of them single case studies. The clinical target populations for BMI-treatment consist primarily of patients with amyotrophic lateral sclerosis (ALS) and severe CNS damage including spinal cord injuries and stroke resulting in substantial deficits in communication and motor function. However, an extensive body of literature started in the 1970s using neurofeedback training. Such training implemented to control various EEG-measures provided solid evidence of positive effects in patients with otherwise pharmacologically intractable epilepsy, attention deficit disorder, and hyperactivity ADHD. More recently, the successful introduction and testing of real-time fMRI and a NIRS-BMI opened an exciting field of interest in patients with psychopathological conditions.
SN 9780123748218
SN 0074-7742
YR 2009
FD 2009
LK https://hdl.handle.net/11556/1514
UL https://hdl.handle.net/11556/1514
LA eng
NO Birbaumer , N , Ramos Murguialday , A , Weber , C & Montoya , P 2009 , Chapter 8 Neurofeedback and Brain-Computer Interface. Clinical Applications . in L Rossini , D Izzo & L Summerer (eds) , International Review of Neurobiology . International Review of Neurobiology , vol. 86 , pp. 107-117 . https://doi.org/10.1016/S0074-7742(09)86008-X
NO This work was supported by the Deutsche Forschungsgemeinschaft (DFG), Bundesministerium für Bildung und Forschung (BMBF, Bernstein-Center for Neurotechnology 01GQ0831), Fatronik, San Sebastian, Spain, Motorike, Cesarea, Israel. Pedro Montoya was supported by Spanish Ministry of Science and European Funds (FEDER) (grant SEJ2007–62312).
DS TECNALIA Publications
RD 26 jul 2024