Assessment of Fractal Characteristics of Locomotor Activity of Geriatric In-Patients With Alzheimer's Dementia

Stefan E Huber; Pierre Sachse; Andreas Mauracher; Josef Marksteiner; Wilfried Pohl; Elisabeth M Weiss; Markus Canazei

doi:10.3389/fnagi.2019.00272

Assessment of Fractal Characteristics of Locomotor Activity of Geriatric In-Patients With Alzheimer's Dementia

Front Aging Neurosci. 2019 Oct 4:11:272. doi: 10.3389/fnagi.2019.00272. eCollection 2019.

Authors

Stefan E Huber^{1

2

3}, Pierre Sachse², Andreas Mauracher¹, Josef Marksteiner⁴, Wilfried Pohl³, Elisabeth M Weiss⁵, Markus Canazei³

Affiliations

¹ Institute of Ion Physics and Applied Physics, University of Innsbruck, Innsbruck, Austria.
² Department of Psychology, University of Innsbruck, Innsbruck, Austria.
³ Bartenbach GmbH, Aldrans, Austria.
⁴ Department of Psychiatry and Psychotherapy A, State Hospital Hall, Hall in Tirol, Austria.
⁵ Department of Psychology, University of Graz, Graz, Austria.

Abstract

Introduction: Many physiological signals yield fractal characteristics, i.e., finer details at higher magnifications resemble details of the whole. Evidence has been accumulating that such fractal scaling is basically a consequence of interaction-dominant feedback mechanisms that cooperatively generate those signals. Neurodegenerative diseases provide a natural framework to evaluate this paradigm when this cooperative function declines. However, methodological issues need to be cautiously taken into account in order to be able to provide reliable as well as valid interpretations of such signal analyses.

Methods: Two conceptually different fractal analyses, i.e., detrended fluctuation analysis (DFA) and analysis of cumulative distributions of durations (CDDs), are applied to actigraphy data of 36 geriatric in-patients diagnosed with dementia. The impact of the used time resolution for data acquisition on the assessed fractal outcome parameters is particularly investigated. Moreover, associations between these parameters and scores from the Mini-Mental-State-Examination and circadian activity parameters are explored.

Results: Both analyses yield significant deviations from (mono-)fractal scaling over the entire considered time range. DFA provides robust measures for the observed break-down of fractal scaling. In contrast, analysis of CDDs results in measures which highly fluctuate with respect to the time resolution of the assessed data which affects also further derived quantities such as scaling exponents or associations with other (clinically relevant) assessed parameters.

Discussion: To scrutinize actigraphic signal characteristics and especially their (deviations from) fractal scaling may be a useful tool for aiding diagnosis, characterization, and monitoring of dementia. However, results may, besides contextual aspects, also substantially depend on specific methodological choices. In order to arrive at both reliable and valid interpretations, these complications need to be carefully elaborated in future research.

Keywords: Alzheimer’s disease; dementia; detrended fluctuation analysis; fractal analysis; fractal scaling; locomotor activity; wrist-actigraphy.