Challenges of Assessing Fluctuations in Actigraphic Acceleration Data Under Sleep and Wakefulness

Human locomotor activity, quantified using the unstandardized method of actigraphy, is frequently analyzed across various disciplines, particularly focusing on its scale-free properties. For multi-day locomotor activity, we have already shown that all differently determined activity data, as well as those of the underlying acceleration signals, exhibit the same universal spectral characteristics, including 1/f noise. In the present study, we have adapted our analytical methodology to the sleep–wake separated examination of 1/f a -like fluctuations commonly employed for activity data in clinical research and extended it to acceleration signals as well. Our systematic analysis revealed that this approach is not only highly sensitive to how sleep periods were identified, but factors such as deterministic measurement errors and the separation of the gravitational component, which are typically negligible in conventional activity-based analyses, can also have a substantial impact when examining acceleration data. Notably, depending on these factors, the observed spectral characteristics of acceleration signals under sleep may even contradict conclusions drawn from activity signal-based studies in the literature, highlighting the necessity of careful methodological considerations.