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Replicating human brain mechanisms towards balancing
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Understanding the performance of the human brain to stabilize the body remains an open fundamental research question. In this article, we study the hypothesis of internal model of the Central Nervous System (CNS) by a novel proposed architecture based on a recurrent neural network. The overall objective of the article and the main contribution stems from demonstrating the capability of replicating the balancing mechanisms of the brain by training the proposed bio-inspired network architecture with human balancing data and in the sequel applying the resulting control structure for controlling a single link inverted pendulum. Towards this direction, the body kinetics and kinematics measurements of forty-five subjects during upright stance trails were collected and utilized for training the proposed neural network. The efficacy of the proposed scheme will be proven through multiple simulation results with a single link inverted pendulum, where it will be demonstrated that the brain-inspired control scheme achieves a proper balance.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Internal model, recurrent neural network, human motor control, postural control
National Category
Engineering and Technology Control Engineering Robotics
Identifiers
URN: urn:nbn:se:ltu:diva-73248OAI: oai:DiVA.org:ltu-73248DiVA, id: diva2:1297089
Conference
17th European Control Conference (ECC)-Naples June 25-28, 2019.
Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2020-01-29
In thesis
1. On mimicking human balance with brain-inspired modeling and control
Open this publication in new window or tab >>On mimicking human balance with brain-inspired modeling and control
2020 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Luleå University of Technology, 2020
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
National Category
Robotics Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-77546 (URN)978-91-7790-522-6 (ISBN)978-91-7790-523-3 (ISBN)
Presentation
2020-03-18, A1547, Luleå, 10:30 (English)
Opponent
Available from: 2020-01-29 Created: 2020-01-29 Last updated: 2020-02-17Bibliographically approved

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Jafari, Hedyeh

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CiteExportLink to record
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Citation style
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Output format
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