01505nas a2200205   4500008004100000022001400041245010600055210006900161260001200230300001400242490000800256520087000264653001501134653000801149653002201157100002601179700002501205700002101230856004801251       2006                        eng d  a0079-612300aBrain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.0 aBraincomputer interface signal processing at the Wadsworth Cente  c02/2006  a411–4190 v1593 aThe Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.10aadaptation10aBCI10aSignal Processing1 aMcFarland, Dennis, J.1 aKrusienski, Dean, J.1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/17071245