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Sensitivity in prediction of human posture by constrained optimization
KTH, School of Engineering Sciences (SCI), Mechanics. KTH Engineering Sciences. (Biomekanik)ORCID iD: 0000-0001-8699-7013
KTH, School of Engineering Sciences (SCI), Mechanics.ORCID iD: 0000-0002-5819-4544
KTH, School of Engineering Sciences (SCI), Mechanics.ORCID iD: 0000-0001-5417-5939
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In a variety of activities of daily living, it is important to be able to stand still in one place. For persons with motion disorders, orthopaedic treatment, which changes geometric or biomechanical properties, can improve the individual's posture and walking ability. Such treatment requires insight into how posture and walking ability are affected. As this is very challenging to observe by the naked eye, engineering tools are increasingly employed to support clinical diagnostics and treatment planning. Because of their potential to help unravel the causal relation between treatment and its outcome, the number of predictive methods are increasing. This study addresses the complications in the creation and analysis of a posture prediction framework. The fmincon optimization function in MATLAB was used in conjunction with a musculoskeletal model in OpenSim. One clear local minimum was found in the form of a symmetric standing posture but perturbation analyses revealed the presence of many other postural congurations, each representing its own unique local minimum in the feasible parameter space. For human postural stance, this can translate to there being many different ways of standing without actually noticing a difference in the efforts required for these poses.

National Category
Applied Mechanics
Research subject
Engineering Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-187486OAI: oai:DiVA.org:kth-187486DiVA: diva2:930561
Funder
Swedish Research Council, 2010-9401-79187-68
Note

This work was financially supported by the Swedish Scientic Council(Vetenskapsrådet) grant no. 2010-9401-79187-68, the ProMobilia handicapfoundation (ref. 13093), Sunnerdahls Handicap foundation (ansökan nr 11/14),and Norrbacka-Eugenia foundation (ansökan nr 218/15).

QC 20160525

Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2016-05-25Bibliographically approved
In thesis
1. Constrained Optimization for Prediction of Posture
Open this publication in new window or tab >>Constrained Optimization for Prediction of Posture
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The ability to stand still in one place is important in a variety of activities of daily living. For persons with motion disorders, orthopaedic treatment, which changes geometric or biomechanical properties, can improve the individual'sposture and walking ability. Decisions on such treatment require insight in how posture and walking ability are aected, however, despite expectations based on experience, it is never a-priori known how a patient will react to a treatment. As this is very challenging to observe by the naked eye, engineering tools are increasingly employed to support clinical diagnostics and treatment planning. The development of predictive simulations allows for the evaluation of the eect of changed biomechanical parameters on the human biological system behavior and could become a valuable tool in future clinical decision making. In the first paper, we evaluated the use of the Zero Moment Point as a computationally inexpensive tool to obtain the ground reaction forces (GRFs) for normal human gait. The method was applied on ten healthy subjects walking in a motion analysis laboratory and predicted GRFs are evaluated against the simultaneously measured force plate data. Apart from the antero-posterior forces, GRFs are well-predicted and errors fall within the error ranges from other published methods. The computationally inexpensive method evaluated in this study can reasonably well predict the GRFs for normal human gait without using prior knowledge of common gait kinetics. The second manuscript addresses the complications in the creation and analysis of a posture prediction framework. The fmincon optimization function in MATLAB was used in conjunction with a musculoskeletal model in OpenSim. One clear local minimum was found in the form of a symmetric standing posture but perturbation analyses revealed the presence of many other postural congurations, each representing its own unique local minimum in the feasible parameter space. For human postural stance, this can translate to there being many different ways of standing without actually noticing a difference in the efforts required for these poses.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. 37 p.
Series
TRITA-MEK, ISSN 0348-467X ; 2016-11
Keyword
Static optimization, Multibody system, Musculoskeletal model
National Category
Applied Mechanics
Research subject
Engineering Mechanics
Identifiers
urn:nbn:se:kth:diva-187488 (URN)978-91-7729-036-0 (ISBN)
Presentation
2016-06-15, E31, Lindstedtsvägen 3, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2010-9401-79187-68
Note

This work was financially supported by the Swedish Scientic Council(Vetenskapsrådet) grant no. 2010-9401-79187-68, the ProMobilia handicapfoundation (ref. 13093), Sunnerdahls Handicap foundation (ansökan nr 11/14),and Norrbacka-Eugenia foundation (ansökan nr 218/15).

Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2016-05-24Bibliographically approved

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