Assessment of the Propagation of Uncertainty on Link Segment Model Results

in Motor Control
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Link segment models are usually used to calculate proximal net reaction forces (PRF), as well as, proximal net moments (PNM). The correlation between electromyographic data and PNM is usually used to verify the model’s results. Nevertheless, this method permits only a qualitative verification of the obtained results. To assess model’s results in a quantitative perspective, another approach is needed. The aim of the current study was to assess the propagation of uncertainty on a link segment model results and identify the main sources of error on the quantification of PRF and PNM. One male performed five repetitions of different upper limb movements. An inverse dynamics approach associate with 3D link segment model was used to quantify PRF and PNM. The results of the model were evaluated by the use of Kleine and McClintock’s equation. The propagation of uncertainty for PRF reached, on average, 0.27 and for PNM, 0.97. The main cause of propagation of uncertainty was associated to the second time derivative calculations. Consequently, it is possible to suggest that the reduction of small distortions of center of mass acceleration will diminish the proximal net moment and proximal reaction force uncertainty values.

Ribeiro is with the Faculdade da Serra Gaúcha, School of Education and Health, Porto Alegre, Brazil And University of Otago, School of Physiotherapy Dunedin, Otago, New Zealand. Loss is with the Federal University of Rio Grande do Sul, School of Physical Education, Porto Alegre, Rio Grande do Sul, Brazil.

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