title: Comparing Postural Stability Entropy Analyses to Differentiate Fallers and Non-fallers.
abstract: The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis.
authors.affiliation: Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Peter C
authors.initials: PC
authors.lastname: Fino
authors.affiliation: Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Ahmad R
authors.initials: AR
authors.lastname: Mojdehi
authors.affiliation: Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Khaled
authors.initials: K
authors.lastname: Adjerid
authors.affiliation: Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Habibi
authors.affiliation: School of Biological and Health Systems Engineering, Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, AZ, 85287, USA. thurmon.lockhart@asu.edu.
authors.forename: Thurmon E
authors.initials: TE
authors.lastname: Lockhart
authors.affiliation: Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
authors.forename: Shane D
authors.initials: SD
authors.lastname: Ross
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D019277:Entropy; D006801:Humans; D008954:Models, Biological; D004856:Postural Balance
keywords: Approximate entropy; Composite multiscale entropy; Elderly; Entropy; Fallers; Multiscale entropy; RQA; Sample entropy