Waiting Time Distributions of Actigraphy Measured Sleep

Sleep quality has a large impact on daily performance and general health. Among the different methods of objectively measuring sleep quality, actigraphy continues to be very popular. It can take continuous activity measurements over several days in order to determine sleep-wake cycles and calculate sleep variables, including the three standard sleep variables used in determining sleep quality: total sleep time, sleep efficiency, and wake-after-sleep onset, in which study analyses use the mean of these variables. In the case of wake-after-sleep onset, which calculates the amount of time between falling asleep and waking up, the average does not characterize wake-after-sleep times as it does not account for the total number of awakenings or the frequencies of wake-after-sleep times. Instead, we recommend using the entire distribution of wake-after-sleep onset times, which we will call waiting time distribution, which better characterizes wake-aftersleep onset than the average value. Sleep quality for each participant was determined by their total sleep time and sleep efficiency. Non-parametric statistics were utilized to determine differences in waiting time distributions between participants with good and poor quality of sleep. Discriminant analysis was performed to show that a distribution of waiting times discriminates better between qualities of sleep than the average wake-after-sleep onset time does. Waiting time distributions were also fit to standard probability distributions for utility and ease of understanding. Analyses show that the waiting time distribution categorizes sleep qualities better than the average wake-after-sleep onset variable, as well as giving more information and better characterizations.