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Báo cáo khoa hoc:" A biologically inspired neural network controller for ballistic arm movements"
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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: A biologically inspired neural network controller for ballistic arm movements | Journal of NeuroEngineering and Rehabilitation BioMed Central Research Open Access A biologically inspired neural network controller for ballistic arm movements Ivan Bernabucci 1 Silvia Conforto1 Marco Capozza2 Neri Accornero2 Maurizio Schmid1 and Tommaso D Alessio1 Address 1Dipartimento di Elettronica Applicata Università degli Studi Roma TRE Roma Italy and 2Dipartimento di Scienze Neurologiche Università La Sapienza Roma Italy Email Ivan Bernabucci - i.bernabucci@uniroma3.it Silvia Conforto - conforto@uniroma3.it Marco Capozza - neri.accornero@uniroma1.it Neri Accornero - neri.accornero@uniroma1.it Maurizio Schmid - schmid@uniroma3.it Tommaso D Alessio - dalessio@uniroma3.it Corresponding author Published 3 September 2007 Received 22 May 2006 _k _. n. lift 1-7.- Accepted 3 September 2007 Journal of NeuroEngineering and Rehabilitation 2007 4 33 doi 10.1186 1743-0003-4-33 This article is available from http www.jneuroengrehab.cOm content 4 1 33 2007 Bernabucci et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background In humans the implementation of multijoint tasks of the arm implies a highly complex integration of sensory information sensorimotor transformations and motor planning. Computational models can be profitably used to better understand the mechanisms sub-serving motor control thus providing useful perspectives and investigating different control hypotheses. To this purpose the use of Artificial Neural Networks has been proposed to represent and interpret the movement of upper limb. In this paper a neural network approach to the modelling of the motor control of a human arm during planar ballistic movements is presented. Methods The developed system is composed of three main computational blocks