Parameter Identification of a Fractional-Order Human-Exoskeleton Coupling Model with the Segmented Form for the Lower Limb

This paper presents a human-exoskeleton coupling model for estimating the human-exoskeleton coupling force. Specifically, to enhance the model's ability to characterize the complex mechanical characteristics of human-exoskeleton coupling, the fractional-order differential term is introduced. Moreover, the coupling model adopts a segmented form to characterize the different mechanical characteristics of front-side and back-side compression in the human-exoskeleton coupling. Using experimental data measured by the self-developed humanexoskeleton coupling measurement platform, the corresponding model parameters for 10 adult male and 10 adult female volunteers (Age: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{23.65 \pm 4.03}$</tex> years, Height: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{165.60 \pm 8.32 cm,}$</tex> Weight: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{62.35\pm 14.09 \text{kg})}$</tex> were identified via Neighborhood Field Optimization (NFO) and Least Squares (LS) methods. Based on the analysis of the estimated root mean square error (RMSE) of the coupling force, it was verified that the coupling force can be estimated accurately based on the proposed fractional-order human-exoskeleton coupling model with the segmented form.

Authors

Institutions

Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/icist63249.2024.10805306
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Parameter Identification of a Fractional-Order Human-Exoskeleton Coupling Model with the Segmented Form for the Lower Limb

Tieshan Li, Qing Guo, Yao Yan, Zhenlei Chen
Elasticity and Material Modeling
article

Parameter Identification of a Fractional-Order Human-Exoskeleton Coupling Model with the Segmented Form for the Lower Limb

Tieshan Li, Qing Guo, Yao Yan, Zhenlei Chen
article en

Abstract

This paper presents a human-exoskeleton coupling model for estimating the human-exoskeleton coupling force. Specifically, to enhance the model's ability to characterize the complex mechanical characteristics of human-exoskeleton coupling, the fractional-order differential term is introduced. Moreover, the coupling model adopts a segmented form to characterize the different mechanical characteristics of front-side and back-side compression in the human-exoskeleton coupling. Using experimental data measured by the self-developed humanexoskeleton coupling measurement platform, the corresponding model parameters for 10 adult male and 10 adult female volunteers (Age: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{23.65 \pm 4.03}$</tex> years, Height: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{165.60 \pm 8.32 cm,}$</tex> Weight: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{62.35\pm 14.09 \text{kg})}$</tex> were identified via Neighborhood Field Optimization (NFO) and Least Squares (LS) methods. Based on the analysis of the estimated root mean square error (RMSE) of the coupling force, it was verified that the coupling force can be estimated accurately based on the proposed fractional-order human-exoskeleton coupling model with the segmented form.

University of Electronic Science and Technology of China (CN)
China Postdoctoral Science Foundation
Zero hunger
Openalex Percentile: Top 77%
Elasticity and Material Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.