title: Ability of static and statistical mechanics posturographic measures to distinguish between age and fall risk.
abstract: Traditional posturographic analysis and four statistical mechanics techniques were applied to center-of-pressure (COP) trajectories of young, older "low-fall-risk" and older "high-fall-risk" individuals. Low-fall-risk older adults were active 3 days per week in a cardiac rehabilitation program, while high-fall-risk older adults were diagnosed with perilymph fistula. Subjects diagnosed with perilymph fistula must have experienced two of the following vestibular findings: constant disequilibrium, positional vertigo and/or a positive fistula test. Non-parametric statistical tests were used to determine whether the posturographic measures could detect differences between the young and older "low-fall-risk" groups (age comparison) and between the older "low-" and "high-risk" groups (risk of falling comparison). The statistical mechanics techniques were more sensitive than the traditional measures: detecting significant differences between the young and older "low-risk" groups, while none of the traditional measures were significantly different. In addition, interpretation of the statistical mechanics techniques may offer more insight into the nature of the process controlling the COP trajectories. However, the methods offered slightly different explanations. For instance, the Hurst rescaled range analysis suggests that the movement of the COP is governed solely by anti-persistent behavior, whereas the stabilogram diffusion analysis suggests a short-term persistence balanced by a long-term anti-persistence. These discrepancies highlight the need for a model that incorporates the biological systems responsible for maintaining balance and experimental methods to directly quantify their status and roles. Until such a model exists, however, the statistical mechanics techniques appear to have some advantages over traditional posturographic measures for studying balance control.
authors.affiliation: Biomedical Engineering Department, School of Biomedical Engineering and Sciences, Wake Forest University Baptist Medical Center, Winston-Salem, NC 27157-1022, USA.
authors.forename: James A
authors.initials: JA
authors.lastname: Norris
authors.forename: Anthony P
authors.initials: AP
authors.lastname: Marsh
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Smith
authors.forename: Robert I
authors.initials: RI
authors.lastname: Kohut
authors.forename: Michael E
authors.initials: ME
authors.lastname: Miller
mesh_terms: D000058:Accidental Falls; D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement; D010808:Physical Examination / Q000379:methods*; D004856:Postural Balance; D011187:Posture; D015995:Prevalence; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D015837:Vestibular Diseases / Q000175:diagnosis / Q000503:physiopathology*