Center of mass approximation and prediction as a function of body acceleration

In order to maintain postural stability, the central nervous system must maintain equilibrium of the total center of body mass (COM) in relation to its base of support. Thus, the trajectory of the COM provides an important measure of postural stability. Three different models were developed to estim...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2006-04, Vol.53 (4), p.686-693
Main Authors: Betker, A.L., Moussavi, Z.M.K., Szturm, T.
Format: Article
Language:English
Subjects:
Acceleration
Accelerometers
Adaptive fuzzy system
Adaptive systems
Adult
Algorithms
Artificial Intelligence
balance
Biological neural networks
center of mass
Central nervous system
Computer Simulation
Female
Fuzzy neural networks
Fuzzy systems
genetic algorithm
Genetic algorithms
Humans
Image Interpretation, Computer-Assisted - methods
Joints - anatomy & histology
Joints - physiology
Male
Models, Biological
Movement - physiology
neural network
Neural networks
Posture - physiology
Stability
Studies
System testing
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Summary:In order to maintain postural stability, the central nervous system must maintain equilibrium of the total center of body mass (COM) in relation to its base of support. Thus, the trajectory of the COM provides an important measure of postural stability. Three different models were developed to estimate the COM and the results tested on 16 subjects: namely a neural network, an adaptive fuzzy interface system and a hybrid genetic algorithm sum-of-sines model. The inputs to the models were acquired via two accelerometers, one representing the trunk segment placed on T2 and the second representing the limb segment placed on the shank below the knee joint. The portability, ease of use and low cost (compared with video motion analysis systems) of the accelerometers increases the range of clinics to which the system will be available. The subjects performed a multisegmental movement task on fixed and foam surfaces, thus covering a relatively wide dynamic scope. The results are encouraging for obtaining COM estimates that have clinical applications; the genetic sum-of-sines model was found to be superior when compared to the other two models.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2006.870222