Defining the rest interval associated with the main sleep period in actigraph scoring.

Actigraphy is increasingly used for sleep monitoring. However, there is a lack of standardized methodology for data processing and analysis, which often makes between study comparisons difficult, if not impossible, and thus open to flawed interpretation. This study evaluated a manual method for detection of the rest interval in actigraph data collected with Actiwatch 2. The rest interval (time in bed), defined as the bedtime and rise time and set by proprietary software, is an essential requirement for the estimation of sleep indices. This study manually and systematically detected the rest interval of 187 nights of recording from seven healthy males and three females, aged 13.5±0.7 (mean ± standard deviation) years. Data were analyzed for agreement between software default algorithm and manual scoring. Inter-rater reliability in manual scoring was also tested between two scorers. Data showed consistency between default settings and manual scorers for bedtime and rise time, but only moderate agreement for the rest interval duration and poor agreement for activity level at bedtime and rise time. Manual detection of rest intervals between scorers showed a high degree of agreement for all parameters (intraclass correlations range 0.864 to 0.995). The findings demonstrate that the default algorithm on occasions was unable to detect rest intervals or set the exact interval. Participant issues and inter-scorer issues also made difficult the detection of rest intervals. These findings have led to a manual detection protocol to define bedtime and rise time, supplemented with an event diary.

The periodicity of sleep duration - an infradian rhythm in spontaneous living.

The sleep-wake cycle is a process not only dictated by homeostatic and circadian factors but also by social and environmental influences. Thus, the total sleep time partly reflects sleep need, which is integral to the dynamics of sleep loss recovery. This study explored the nature of the observed oscillations in total sleep time in healthy adults under spontaneous living conditions. Actigraph-measured sleep data for 13 healthy young male adults were collected over 14 consecutive days and analyzed for habitual sleep duration. The total sleep time periodicity was modeled using the cosinor method for each individual across the 14 days. The findings confirm the existence of periodicity in habitual sleep duration as there were clear periodic patterns in the majority of the participants. Although exclusive to each individual, the observed oscillations may be a resultant response of homeostatic sleep need, circadian timing, and/or social and environmental influences. These findings instigate further indepth studies into the periodicity of sleep duration in healthy individuals to provide a better understanding of sleep need in short versus long sleepers, in predicting work performance, and reducing sleepiness-related accidents following shift work, and how this periodicity may impact sleep treatment outcome in clinical populations.