Bayesian inference of physiologically meaningful parameters from body sway measurements

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http://hdl.handle.net/10138/211417

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Tietavainen , A , Gutmann , M U , Keski-Vakkuri , E , Corander , J & Haeggstrom , E 2017 , ' Bayesian inference of physiologically meaningful parameters from body sway measurements ' , Scientific Reports , vol. 7 , 3771 . https://doi.org/10.1038/s41598-017-02372-1

Title: Bayesian inference of physiologically meaningful parameters from body sway measurements
Author: Tietavainen, A.; Gutmann, M. U.; Keski-Vakkuri, E.; Corander, J.; Haeggstrom, E.
Contributor: University of Helsinki, Department of Physics
University of Helsinki, Department of Physics
University of Helsinki, Department of Mathematics and Statistics
University of Helsinki, Department of Physics
Date: 2017-06-19
Language: eng
Number of pages: 14
Belongs to series: Scientific Reports
ISSN: 2045-2322
URI: http://hdl.handle.net/10138/211417
Abstract: The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects. Our method provides a full statistical characterization of the uncertainty related to all model parameters as quantified by posterior probability density functions, which is useful for comparisons across subjects and test settings. The ability to infer intractable control models from sensor data opens new possibilities for monitoring and predicting body status in health applications.
Subject: OF-PRESSURE TRAJECTORIES
MONTE-CARLO METHODS
POSTURAL CONTROL
STATIC POSTUROGRAPHY
INTERMITTENT CONTROL
PARKINSONS-DISEASE
MULTIPLE-SCLEROSIS
STRANGE ATTRACTORS
SLEEP-DEPRIVATION
MUSCLE-STIFFNESS
114 Physical sciences
3112 Neurosciences
112 Statistics and probability
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