A Multidimensional Approach to Develop Sway Index Using Gaussian Mixture Model: A Way of Postural Sway Measurement and Analysis in Different Age Groups

Abstract

Many classical postural sway measures are based on linear analysis of different temporal characteristics of the body’s center of pressure (CoP). In some of the classical sway analysis methods, the anterior–posterior and the mediolateral aspects are analyzed separately. While these classical measures are found to be affected by aging, they cover different aspects of stability. Moreover, linear postural sway analysis is not efficient due to complexity of the human physiological functions. This study developed a single sway index based on the nonlinear analysis of the multidimensional CoP data and compared it in different participant age groups in different standing tests. The sway index performance was compared with six classical sway measures and six universal sway parameters. In all, 17 younger active lifestyle participants (31 ± 5.7), 12 participants age between 50 and 60 years (56.2 ± 3.3), and 32 older participants age 60 years and above (69.6 ± 6.2) were recruited for this study. Participants were asked to undergo three standing tests of double stance, single stance, and tandem stance all with eyes closed for 20 s. Using a global machine-learnt Gaussian mixture model, the multidimensional CoP data were clustered, and consequently an index was derived based on the results. Most classical and universal sway measures in the single stance and tandem stance were found to be significantly different in younger participants compared with the older ones. Our proposed sway index was significantly different in younger participants compared with 50–60 years participants in addition to older participants. The sway index also outperformed all classical and universal sway measures in the single and tandem stance tests with the sensitivity of 90.9% and 87.5%, the specificity of 82.4% and 84.3%, and AUC of 0.90 (95% CI, 0.81–1) and 0.91 (95% CI, 0.82–0.99), respectively. The findings demonstrated a strong potential of the sway index to be used as a single yet effective sway measurement.