ArticleScientific reports2024
General spectral characteristics of human activity and its inherent scale-free fluctuations.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Subtle to significant: Enhancing heaviness perception with stochastic resonance.Journal of experimental psychology. Human perception and performance · 2026Article
- An Autonomous Clock that Controls Genetic Information Flow and Cellular Proteostasis.Advances in experimental medicine and biology · 2026Review
- The Impact of Quantifying Human Locomotor Activity on Examining Sleep-Wake Cycles.Sensors (Basel, Switzerland) · 2025Article
- Explainable AI for Depression Detection and Severity Classification From Activity Data: Development and Evaluation Study of an Interpretable Framework.JMIR mental health · 2025Article
- Hierarchical organization of human physical activity.Scientific reports · 2024Article
- The effects of right temporoparietal junction stimulation on embodiment, presence, and performance in teleoperation.AIMS neuroscience · 2024Article
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3 authors.
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Abstract
The scale-free nature of daily human activity has been observed in different aspects; however, the description of its spectral characteristics is incomplete. General findings are complicated by the fact that-although actigraphy is commonly used in many research areas-the activity calculation methods are not standardized; therefore, activity signals can be different. The presence of 1/f noise in activity or acceleration signals was mostly analysed for short time windows, and the complete spectral characteristic has only been examined in the case of certain types of them. To explore the general spectral nature of human activity in greater detail, we have performed Power Spectral Density (PSD) based examination and Detrended Fluctuation Analysis (DFA) on several-day-long, triaxial actigraphic acceleration signals of 42 healthy, free-living individuals. We generated different types of activity signals from these, using different acceleration preprocessing techniques and activity metrics. We revealed that the spectra of different types of activity signals generally follow a universal characteristic including 1/f noise over frequencies above the circadian rhythmicity. Moreover, we discovered that the PSD of the raw acceleration signal has the same characteristic. Our findings prove that the spectral scale-free nature is generally inherent to the motor activity of healthy, free-living humans, and is not limited to any particular activity calculation method.
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