TY - GEN
T1 - The application of a real-time rapid-prototyping environment for the behavioral rehabilitation of a lost brain function in rats
AU - Pruckl, R.
AU - Grünbacher, E.
AU - Ortner, R.
AU - Taub, A. H.
AU - Hogri, R.
AU - Magal, A.
AU - Segalis, E.
AU - Zreik, M.
AU - Nossenson, N.
AU - Herreros, I.
AU - Giovannucci, A.
AU - Almog, R. Ofek
AU - Bamford, S.
AU - Marcus-Kalish, M.
AU - Shacham, Y.
AU - Verschure, P. F.M.J.
AU - Messer, H.
AU - Mintz, M.
AU - Scharinger, J.
AU - Silmon, A.
AU - Guger, C.
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - In this paper we propose a Rapid Prototyping Environment (RPE) for real-time biosignal analysis including ECG, EEG, ECoG and EMG of humans and animals requiring a very precise time resolution. Based on the previous RPE which was mainly designed for developing Brain Computer Interfaces (BCI), the present solution offers tools for data preprocessing, analysis and visualization even in the case of high sampling rates and furthermore tools for precise cognitive stimulation. One application of the system, the analysis of multi-unit activity measured from the brain of a rat is presented to prove the efficiency of the proposed environment. The experimental setup was used to design and implement a biomimetic, biohybrid model for demonstrating the recovery of a learning function lost with age. Throughout the paper we discuss the components of the setup, the software structure and the online visualization. At the end we present results of a real-time experiment in which the model of the brain learned to react to he acquired signals.
AB - In this paper we propose a Rapid Prototyping Environment (RPE) for real-time biosignal analysis including ECG, EEG, ECoG and EMG of humans and animals requiring a very precise time resolution. Based on the previous RPE which was mainly designed for developing Brain Computer Interfaces (BCI), the present solution offers tools for data preprocessing, analysis and visualization even in the case of high sampling rates and furthermore tools for precise cognitive stimulation. One application of the system, the analysis of multi-unit activity measured from the brain of a rat is presented to prove the efficiency of the proposed environment. The experimental setup was used to design and implement a biomimetic, biohybrid model for demonstrating the recovery of a learning function lost with age. Throughout the paper we discuss the components of the setup, the software structure and the online visualization. At the end we present results of a real-time experiment in which the model of the brain learned to react to he acquired signals.
KW - Biomedical Engineering
KW - Biomedical Systems
KW - Neurological analysis
KW - Rapid Prototyping
KW - Real-Time
UR - http://www.scopus.com/inward/record.url?scp=79961154309&partnerID=8YFLogxK
U2 - 10.1109/CCMB.2011.5952121
DO - 10.1109/CCMB.2011.5952121
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AN - SCOPUS:79961154309
SN - 9781424498918
T3 - IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CCMB 2011: 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain
SP - 128
EP - 135
BT - IEEE SSCI 2011 - Symposium Series on Computational Intelligence - CCMB 2011
T2 - Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, CCMB 2011
Y2 - 11 April 2011 through 15 April 2011
ER -