Literature DB >> 19862548

MODEM: a multi-agent hierarchical structure to model the human motor control system.

Mehran Emadi Andani1, Fariba Bahrami, Parviz Jabehdar Maralani, Auke Jan Ijspeert.   

Abstract

In this study, based on behavioral and neurophysiological facts, a new hierarchical multi-agent architecture is proposed to model the human motor control system. Performance of the proposed structure is investigated by simulating the control of sit to stand movement. To develop the model, concepts of mixture of experts, modular structure, and some aspects of equilibrium point hypothesis were brought together. We have called this architecture MODularized Experts Model (MODEM). Human motor system is modeled at the joint torque level and the role of the muscles has been embedded in the function of the joint compliance characteristics. The input to the motor system, i.e., the central command, is the reciprocal command. At the lower level, there are several experts to generate the central command to control the task according to the details of the movement. The number of experts depends on the task to be performed. At the higher level, a "gate selector" block selects the suitable subordinate expert considering the context of the task. Each expert consists of a main controller and a predictor as well as several auxiliary modules. The main controller of an expert learns to control the performance of a given task by generating appropriate central commands under given conditions and/or constraints. The auxiliary modules of this expert learn to scrutinize the generated central command by the main controller. Auxiliary modules increase their intervention to correct the central command if the movement error is increased due to an external disturbance. Each auxiliary module acts autonomously and can be interpreted as an agent. Each agent is responsible for one joint and, therefore, the number of the agents of each expert is equal to the number of joints. Our results indicate that this architecture is robust against external disturbances, signal-dependent noise in sensory information, and changes in the environment. We also discuss the neurophysiological and behavioral basis of the proposed model (MODEM).

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Year:  2009        PMID: 19862548     DOI: 10.1007/s00422-009-0342-5

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  2 in total

1.  Trajectory of human movement during sit to stand: a new modeling approach based on movement decomposition and multi-phase cost function.

Authors:  Mohsen Sadeghi; Mehran Emadi Andani; Fariba Bahrami; Mohamad Parnianpour
Journal:  Exp Brain Res       Date:  2013-06-27       Impact factor: 1.972

2.  How does the CNS control arm reaching movements? Introducing a hierarchical nonlinear predictive control organization based on the idea of muscle synergies.

Authors:  Sedigheh Dehghani; Fariba Bahrami
Journal:  PLoS One       Date:  2020-02-05       Impact factor: 3.240

  2 in total

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