The Impact of Acceleration Measurement Parameters on Multiday Actigraphic Data across Sleep and Wakeful Periods

Although actigraphy is widespread across disciplines to quantify human locomotor activity, its methodology remains unstandardized: the measurement parameters used to record acceleration and the methods used to compress it into epoch-level activity signals vary substantially across manufacturers. While we previously characterized the impact of the latter by emulating device-specific activity determination methods, the effects of acceleration sampling frequency, bit resolution, and full-scale range remain unclear. To systematically investigate these effects, we had to characterize the correlation-based relationships among activity determination methods during sleep and wakefulness to distinguish differences arising from their distinct motion characteristics from those introduced by reducing acceleration data quality. Then, by modifying measurement parameters to emulate different hardware settings, we found that parameter alterations had no effect over multiday and wakeful timeframes. Even when focusing on sleep periods, modifying the measurement parameters affected only a few activity determination methods, with the extent of these effects also influenced by the post-calibration of acceleration data. Overall, how activity is derived from acceleration has a substantially greater influence on the resulting activity signals than the measurement parameters used to record the underlying acceleration data, although high-fidelity acceleration collection remains particularly important for calibration-dependent activity determination methods in sleep-focused analyses.