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‘Blip’ analysis, fast wavelet transformations (FWT) and correlation analysis have all been used to actigraphically assess the impact one person is having on another's sleep, yet no review exists as to the differences between, and applicability of, these methods for investigating couples’ sleep. Using actigraphy data and audio sleep diaries collected from 18 couples, this paper provides such a review. This paper constructs and assesses two novel, analytical methods: Lotjonen's sleep/wake algorithm, and the partner impact on sleep wake analysis (PISWA). Both ‘blip’ analysis and correlation suggest that the strongest relationship between bed partners occurs on an epoch-to-epoch basis. However, ‘blips’ deal strictly with onset of movement and fail to incorporate strength and duration of movement. Conversely, correlation analysis incorporates some elements of strength and duration of movement but makes identification of onset problematic. FWT offer useful ‘relativistic’ pattern recognition, identifying onset, strength and duration of movement, but are difficult to quantify. Although audio diary data support the potential of Lotjonen's sleep/wake algorithm to identify sleep non-movement, sleep movement, wake non-movement (or quiet wakefulness) and wake movement, the problem remains that this method also relies on visualization. Of most promise, we argue, is the PISWA, which examines ‘impact’ of bed partners through incorporating elements of ‘blip’ analysis and the sleep/wake algorithm. [ABSTRACT FROM AUTHOR]

Various definitions of arousals have been used in infants. An international group of experts has worked on a consensus for the scoring of arousals in healthy infants, aged between 1 and 6 months. This opinion paper summarizes the consensus statement on the scoring of arousal. The paper reviews recommended techniques for the recording of arousal in infants. Scoring includes the differentiation between subcortical activation, with no visible change n the electroencephalograph (EEG) recording, and cortical arousals associated with EEG changes. The arousals are further scored as spontaneous or induced, according to environmental conditions. Potential limitations to the method are discussed, with the hope that this document could contribute to promote further progresses in the scoring of infants arousals from sleep. [ABSTRACT FROM AUTHOR]

Humans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance ( UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation ( TSD) and (ii) chronic sleep restriction ( CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over non-individualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions. [ABSTRACT FROM AUTHOR]

The effect of sleep loss on reaction time (RT) performance varies as a function of age, with RTs of older subjects typically showing less decrement (relative to rested baseline) than those of younger subjects. In the current paper, we examined the nature of this relationship in a 7-day sleep restriction study. The number of repeated measures made it possible to model both intra-individual trajectories over days and individual differences in these trajectories. Results revealed (a) consistent individual differences in RT patterns over time after controlling for experimental design effects; (b) less cumulative RT decline among older individuals regardless of the degree of sleep restriction; and (c) consistent individual variability in performance patterns even after accounting for the effects of age. [ABSTRACT FROM AUTHOR]