Multiscale entropy derived complexity index analysis demonstrates significant mediolateral sway in persons with multiple sclerosis compared to healthy controls

Clinical assessment of Multiple Sclerosis relies heavily on the Expanded Disability Status Scale, a non-linear rating system based on physician assessment of disease progression and walking ability. This inherently makes this method both subjective and limited in repeatability. This study developed a technically derived outcome measure of posture to compare a cohort of Multiple Sclerosis and Control subjects during an Eyes-Open and Eyes-closed task. Analysing traditional sway parameters and a multiscale entropy derived complexity index of posturography showed a significant difference in medio-lateral sway between groups during the Eyes-Open condition. This technically derived outcome measure may be of clinical benefit in the longitudinal assessment of the functional impact of balance in MS cohorts and assist in the evaluation of pharmaceutical and rehabilitation interventions.

[1]  J. Sosnoff,et al.  Deficits in medio-lateral balance control and the implications for falls in individuals with multiple sclerosis. , 2016, Gait & posture.

[2]  Max A. Little,et al.  Technology in Parkinson's disease: Challenges and opportunities , 2016, Movement disorders : official journal of the Movement Disorder Society.

[3]  W. L. Benedict,et al.  Multiple Sclerosis , 2007, Journal - Michigan State Medical Society.

[4]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[5]  Maria Crotty,et al.  Association of Postural Sway with Disability Status and Cerebellar Dysfunction in People with Multiple Sclerosis: A Preliminary Study. , 2015, International journal of MS care.

[6]  A. Goldberger,et al.  Loss of 'complexity' and aging. Potential applications of fractals and chaos theory to senescence. , 1992, JAMA.

[7]  Fary Khan,et al.  Rehabilitation in Multiple Sclerosis: A Systematic Review of Systematic Reviews. , 2017, Archives of physical medicine and rehabilitation.

[8]  N. Kishk,et al.  Assessment of postural balance in multiple sclerosis patients , 2019, The Egyptian Journal of Neurology, Psychiatry and Neurosurgery.

[9]  Jacob J. Sosnoff,et al.  Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach , 2018, Scientific Reports.

[10]  Manuel Duarte Ortigueira,et al.  On the HHT, its problems, and some solutions , 2008 .

[11]  John H. J. Allum,et al.  Trunk sway in mildly disabled multiple sclerosis patients with and without balance impairment , 2011, Experimental Brain Research.

[12]  Gyrd Thrane,et al.  Spasticity, gait, and balance in patients with multiple sclerosis: A cross-sectional study. , 2019, Physiotherapy research international : the journal for researchers and clinicians in physical therapy.

[13]  Madalena Costa,et al.  Multiscale entropy analysis of complex physiologic time series. , 2002, Physical review letters.

[14]  B. Çınar,et al.  What We Learned from The History of Multiple Sclerosis Measurement: Expanded Disability Status Scale. , 2018, Noro psikiyatri arsivi.

[15]  D. Ontaneda,et al.  Clinical trials in progressive multiple sclerosis: lessons learned and future perspectives , 2015, The Lancet Neurology.

[16]  Richard B. Reilly,et al.  Complexity based measures of postural stability provide novel evidence of functional decline in fragile X premutation carriers , 2019, Journal of NeuroEngineering and Rehabilitation.