{Reference Type}: Journal Article
{Title}: The use of nonlinear analysis in understanding postural control: A scoping review.
{Author}: Veronez SO;do Espirito-Santo CC;Dantas AFOA;Pereira ND;Ilha J;
{Journal}: Hum Mov Sci
{Volume}: 96
{Issue}: 0
{Year}: 2024 Jun 20
{Factor}: 2.397
{DOI}: 10.1016/j.humov.2024.103246
{Abstract}: Nonlinear analyses have emerged as an approach to unraveling the intricate dynamics and underlying mechanisms of postural control, offering insights into the complex interplay of physiological and biomechanical factors. However, achieving a comprehensive understanding of the application of nonlinear analysis in postural control studies remains a challenge due to the various nonlinear measurement methods currently available. Thus, this scoping review aimed to identify existing nonlinear analyses used to study postural control in both dynamic and quiet tasks, and to summarize and disseminate the available literature on the use of nonlinear analysis in postural control. For this purpose, a scoping review was conducted and reported following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist and Explanation. Searches were conducted up to July 2023 on PubMed/Medline, Embase, CINAHL, Web of Science, and Google Scholar databases, resulting in the inclusion of 397 unique studies. The main classes employed among the studies were entropy-based, fractal-based, quantification of recurrence plots, and quantification of stability, with a total of 91 different algorithms distributed among these classes. The most common condition used to study postural control was quiet standing, followed by dynamic standing and gait tasks. Although various algorithms were utilized for this purpose, sample entropy was employed in 43% of studies to explore mechanisms related to postural control. Among them, 28% were in quiet standing, 3.27% were in dynamic standing, and 4.78% to study postural control during the gait. The results also provide insights into nonlinear analysis for future studies, concerning the complexity and interactions within the postural control system across various task demands.