Control of arm movement using population of neurons

Z. Nenadic; C. H. Anderson; B. Ghosh

doi:10.1016/S0895-7177(02)00084-5

Control of arm movement using population of neurons

Z. Nenadic, C. H. Anderson, B. Ghosh

Mathematics and Statistics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Movements of the human arm in a horizontal plane are very stereotyped in the sense that the corresponding paths are mainly straight lines and the velocity profiles are "bell-shaped like" functions. A dynamics of two link model of the human arm has been studied with the goal of synthesizing the torques which accomplish the desired transfer. The parameters of the desired trajectory, as well as the system variables, are encoded using populations of a different number of neurons. The driving torques are generated from the corresponding activities using an optimal decoding rule.

Original language	English
Pages (from-to)	1261-1269
Number of pages	9
Journal	Mathematical and Computer Modelling
Volume	35
Issue number	11-12
DOIs	https://doi.org/10.1016/S0895-7177(02)00084-5
State	Published - May 16 2002

Keywords

Internal dynamics
Neural activities
Optimal decoding
Path plan

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10.1016/S0895-7177(02)00084-5

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AU - Anderson, C. H.

AU - Ghosh, B.

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AB - Movements of the human arm in a horizontal plane are very stereotyped in the sense that the corresponding paths are mainly straight lines and the velocity profiles are "bell-shaped like" functions. A dynamics of two link model of the human arm has been studied with the goal of synthesizing the torques which accomplish the desired transfer. The parameters of the desired trajectory, as well as the system variables, are encoded using populations of a different number of neurons. The driving torques are generated from the corresponding activities using an optimal decoding rule.

KW - Internal dynamics

KW - Neural activities

KW - Optimal decoding

KW - Path plan

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SN - 0895-7177

IS - 11-12

ER -

Control of arm movement using population of neurons

Abstract

Keywords

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