A novel quantitative method for coding epochs of active and quiet sleep in infants using respiration is reported. The approach uses the variance of the instantaneous breathing rate within brief epochs of sleep. Variances are normalized within subject by dividing by the 75th percentile variance across epochs. Then, a normalized variance active sleep threshold of 0.29 was determined to produce the highest concordance with a method based on visual inspection of respiratory variability (100% and 90% for quiet and active sleep, respectively). The method was independently validated by comparing to standard polysomnographic state coding (87% and 80% concordance for quiet and active sleep) as well as with behavioral state coding (92% and 78% for quiet and active sleep). Validity was also demonstrated by showing that sleep states identified by the method resulted in the expected state differences in infant heart rate variability and electrocortical activity.
Keywords: EEG power; automated state scoring; breathing rate; heart rate variability; human infant; sleep state.
© 2016 Wiley Periodicals, Inc.