TY - GEN
T1 - Design and implementation of a human ECoG simulator for testing brain-machine interfaces
AU - Fifer, Matthew S.
AU - Milsap, Griffin W.
AU - Greenwald, Elliot
AU - McMullen, David P.
AU - Anderson, William S.
AU - Thakor, Nitish V.
AU - Crone, Nathan E.
AU - Vinjamuri, Ramana
PY - 2013
Y1 - 2013
N2 - This paper presents the design and implementation of a signal simulator that emulates event-related human electrocorticographic (ECoG) signals. This realtime simulator renders a representative model of human ECoG encompassing prominent physiological modulation in the time domain (e.g., event-related potentials, or ERPs) and the frequency domain (e.g., alpha/mu, beta, and high gamma band). The simulated signals were generated in a MATLAB SIMULINK framework and output through a National Instruments PCI card for recording by a standard research-grade ECoG amplifier system. Trial-averaged event-related spectrograms computed offline from simulated signals exhibit characteristics similar to those of experimental human ECoG recordings. The presented simulator can serve as a useful tool for testing real-time brain-machine interface (BMI) applications. It can also serve as a potential framework for future implementation of neuronal models for generation of extracellular field potentials.
AB - This paper presents the design and implementation of a signal simulator that emulates event-related human electrocorticographic (ECoG) signals. This realtime simulator renders a representative model of human ECoG encompassing prominent physiological modulation in the time domain (e.g., event-related potentials, or ERPs) and the frequency domain (e.g., alpha/mu, beta, and high gamma band). The simulated signals were generated in a MATLAB SIMULINK framework and output through a National Instruments PCI card for recording by a standard research-grade ECoG amplifier system. Trial-averaged event-related spectrograms computed offline from simulated signals exhibit characteristics similar to those of experimental human ECoG recordings. The presented simulator can serve as a useful tool for testing real-time brain-machine interface (BMI) applications. It can also serve as a potential framework for future implementation of neuronal models for generation of extracellular field potentials.
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U2 - 10.1109/NER.2013.6696182
DO - 10.1109/NER.2013.6696182
M3 - Conference contribution
AN - SCOPUS:84897704614
SN - 9781467319690
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 1311
EP - 1314
BT - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
T2 - 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Y2 - 6 November 2013 through 8 November 2013
ER -