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Human sit-to-stand transfer modeling towards intuitive and biologically-inspired robot assistance
Authors
A Kralj
Angelika Peer
+32 more
Christian Werner
D Mayne
E Todorov
ER Ikeda
F Bahrami
H Hirshfeld
J Kuzelicki
JM Guralnik
K Iqbal
K Mombaur
K Mombaur
Klaus Hauer
KLH Hoang
KM Kerr
L Schwickert
M Galli
M Schenkman
M Vukobratovic
MF Folstein
Milad Geravand
MW Rodosky
P Leva De
P Millington
Peter Zeno Korondi
S Yoshioka
S Yoshioka
T Kotake
U Lindemann
V Zatsiorsky
W Mathiyakom
WGM Janssen
ZL Liao
Publication date
1 January 2017
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
© 2016, Springer Science+Business Media New York. Sit-to-stand (STS) transfers are a common human task which involves complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, energy consumption, smoothness of motion and control and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy and patient/elderly subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. Finally, the proposed STS model is used to determine optimal assistive strategies suitable for either a person with specific body segment weakness or a more general weakness. These strategies are implemented on a robotic mobility assistant and are intensively evaluated by 33 elderlies, mostly not able to perform unassisted STS transfers. The validation results show a promising STS transfer success rate and overall user satisfaction
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UWE Bristol Research Repository
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Crossref
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info:doi/10.1007%2Fs10514-016-...
Last time updated on 17/09/2020
Archivio istituzionale della ricerca - Università di Trieste
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