Non-Linear Techniques Reveal Adaptive and Maladaptive Postural Control Dynamics in Persons with Multiple Sclerosis
| Autor: | Michael Ab, Van Emmerik Rea, Scott Wd |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
media_common.quotation_subject Machine learning computer.software_genre 01 natural sciences Adaptability 010305 fluids & plasmas Postural control Multiscale entropy 03 medical and health sciences 0302 clinical medicine 0103 physical sciences medicine media_common Physiological function business.industry Multiple sclerosis Disease progression medicine.disease Nonlinear system Detrended fluctuation analysis Data mining Artificial intelligence business computer 030217 neurology & neurosurgery |
| Zdroj: | Journal of Multiple Sclerosis. |
| ISSN: | 2376-0389 |
| DOI: | 10.4172/2376-0389.1000177 |
| Popis: | In this commentary we discuss how complex and nonlinear analysis methods, multiscale entropy (MSE) and detrended fluctuation analysis (DFA) can provide insights into postural changes in people with multiple sclerosis (MS). Here we highlight key methodological considerations for both MSE and DFA, specifically discuss how MS and aging impact the complexity and adaptability of postural control. As MSE and DFA are both sensitive to technical considerations, we directly address how changes in signal processing and equation parameterization impact outcomes and how these may in turn influence the interpretation of results. Furthermore, we identify how MSE and DFA identify different features of disease progression and how the associated breakdowns in physiological function manifest as postural fluctuation changes within and between different time scales. Finally, we propose a framework that combines these techniques to identify the adaptive and maladaptive changes that accompany MS progression. |
| Databáze: | OpenAIRE |
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