Deep Learning based Model Identification System Exploits the Modular Structure of a Bio-inspired Posture Control Model for Humans and Humanoids

Vittorio Lippi

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Paper

Deep Learning based Model Identification System Exploits the Modular Structure of a Bio-inspired Posture Control Model for Humans and Humanoids

Topics: Bioinformatics and Systems Biology; Biometrics; Deep Learning and Neural Networks; Robotics; Signal Processing

In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 540-547, 2021

Author: Vittorio Lippi

Affiliation: Neurological University Clinic, University of Freiburg, Freiburg im Breisgau, Germany

Keyword(s): Posture Control, Deep Learning, System Identification, Parametric Nonlinear System.

Abstract: This work presents a system identification procedure based on Convolutional Neural Networks (CNN) for human posture control using the DEC (Disturbance Estimation and Compensation) parametric model. The modular structure of the proposed control model inspired the design of a modular identification procedure, in the sense that the same neural network is used to identify the parameters of the modules controlling different degrees of freedom. In this way the presented examples of body sway induced by external stimuli provide several training samples at once.

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Paper citation in several formats:

Lippi, V. (2021). Deep Learning based Model Identification System Exploits the Modular Structure of a Bio-inspired Posture Control Model for Humans and Humanoids. In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-486-2; ISSN 2184-4313, SciTePress, pages 540-547. DOI: 10.5220/0010245405400547

@conference{icpram21,
author={Vittorio Lippi},
title={Deep Learning based Model Identification System Exploits the Modular Structure of a Bio-inspired Posture Control Model for Humans and Humanoids},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2021},
pages={540-547},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010245405400547},
isbn={978-989-758-486-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Deep Learning based Model Identification System Exploits the Modular Structure of a Bio-inspired Posture Control Model for Humans and Humanoids
SN - 978-989-758-486-2
IS - 2184-4313
AU - Lippi, V.
PY - 2021
SP - 540
EP - 547
DO - 10.5220/0010245405400547
PB - SciTePress