ArticleFrontiers in aging neuroscience2019
Assessment of Fractal Characteristics of Locomotor Activity of Geriatric In-Patients With Alzheimer's Dementia.
Article in Frontiers in aging neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Determinants of fractal motor activity regulation: insights from a large community-dwelling multi-ethnic population.Research square · 2026Article
- Detecting the fractal physical activity pattern in aged adults with cerebral small vessel disease.Frontiers in aging neuroscience · 2025Article
- General spectral characteristics of human activity and its inherent scale-free fluctuations.Scientific reports · 2024Article
- Fractal complexity of daily physical activity and cognitive function in a midlife cohort.Scientific reports · 2023Article
- Insulin signaling shapes fractal scaling of C. elegans behavior.Scientific reports · 2022Article
- Complexity of Body Movements during Sleep in Children with Autism Spectrum Disorder.Entropy (Basel, Switzerland) · 2021Article
- Nonparametric time series summary statistics for high-frequency accelerometry data from individuals with advanced dementia.PloS one · 2020Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMany 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.
methodsTwo 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.
resultsBoth 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.
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