Nathan H. C. Zebendo 
, Jonathan N. Gois , Diego R. G. Gonzalez , Wesley L. Passos , Gabriel M. Araujo & Amaro A. de Lima
Abstract: This paper proposes automatically estimating postural balance test scores and their subsystems using stabilometry results. These results are obtained using a force platform that captures the variation in the person’s center of pressure position over time. On the other hand, postural balance test scores are conducted by qualified health professionals and comprise the assessment of various subsystems that can provide specific diagnoses separately and, when combined, can form a comprehensive assessment method called the MINI-BESTest. Early diagnosis makes it possible to identify the risk of falls due to advancing age or related limiting illnesses. Using a hierarchical approach, which makes it possible to automate the process and reduce the subjectivity of the assessment, it is possible to estimate the MINI-BESTest score and its Reactive Postural Control subsystem with an accuracy of, respectively, 17% and 20% higher than the state-of-the-art.
Keywords: Stabilometry; force platform; MINI-BESTest; random forest; support vector regression.
DOI code: 10.21528/lnlm-vol23-no2-art1
PDF file: vol23-no2-art1.pdf
BibTex file: vol23-no2-art1.bib