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Obstructive sleep apnoea (OSA) is associated in 80% of the cases with more and longer apnoeas/hypopneas in the supine position. Some effort has been made to find an effective treatment that improves OSA by correcting the sleep position. So far, the most used treatment is avoidance of sleeping supine, although there is a lack of compliance due to discomfort and sleep disruption. Researchers recently investigated the effect of the head/neck position on OSA. One study found an improvement of the apnoea/hypopnea index (AHI) and sleep quality after promoting neck extension with a custom fitted cervical pillow (Kushida, C.A. et al. Sleep and Breathing 2001; 5(2): 71-78). The objective of this study was to assess the effect of cervical positioning on OSA through the use of an adaptive bedding system which promotes neck extension in the supine position. Seven male OSA patients were studied. The group included 2 mild, 3 moderate and 2 severe patients. They spent 3 nights in a sleep center: an adaptation, a reference (REF) and a steering night (AS), during which the shoulder-neck region of the bed was automatically adapted to promote neck extension when detecting a supine position of the subject. Sleep and breathing parameters were obtained by means of questionnaires and PSG. Overall, subjects showed no significant improvement in AHI between the reference (24.1 ± 14.3) and steering night (25.4 ± 15.5; p=.866). However, detailed evaluation identified an improvement in the apnoea index during supine positions in the steering night (REF: 5.3 ± 4.5; AS: 1.3 ± 1.8; pThese preliminary findings indicate that the bedding system might improve supine-related AHI, but further experiments are needed.

Introduction and objectives: Despite a long history of interest in emotion regulation as well as in the mechanisms that regulate sleep, the relationship between emotion regulation and sleep is not well described. Material and methods: To get insight in this relationship, we examined the effects of pre-sleep painful emotion (i.e., a failure-experience), moderating effects of induced emotion regulation in the recovery from the experience and the effects in shaping sleep physiology assessed by polysomnography (EEG). Results: As hypothesized, results indicate that participants who received experiential emotion regulation showed less fragmentation of sleep by a longer Total Sleep Time, higher Sleep Efficiency with more % REM sleep and Slow Wave Sleep than participants who received analytical emotion regulation. For the group of participants who received experiential emotion regulation, due to its regulatory effect, sleep parameters did not differ between the baseline and the failure night. By contrast, analytical emotion regulation was associated with more Awakenings, more % Time Awake, more Waso (Awake after Sleep Onset), and a longer Latency to Slow Wave-Sleep in comparison with experiential emotion regulation. Conclusion: In the recovery of a painful experience, a beneficial effect of experiential emotion regulation has been observed on sleep physiology, compared to cognitive analytical emotion regulation.

Despite a long history of interest in emotion regulation as well as in the mechanisms that regulate sleep, the relationship between emotion regulation and sleep is not well described. The present study investigated whether the induction of 'experiential' versus 'cognitive' emotion regulation buffers the impact of a stressful failure experience on (1) emotional experience and rumination and (2) sleep structure by EEG polysomnography. 28 healthy volunteers participated in this study. As expectedhypothesized, results indicated that participants who received experiential emotion regulation showed less fragmentation of sleep by a longer Total Sleep Time, higher Sleep Efficiency with more % REM sleep and Slow Wave Sleep than participants who received analytical emotion regulation. For the group of participants who received experiential emotion regulation, due to its regulatory effect, sleep parameters did not differ between the baseline and the failure night. By contrast, analytical emotion regulation was associated more Awakenings, more % Time Awake, more Time Awake after Sleep Onset, and a longer Latency to Slow Wave-Sleep than in comparison with experiential emotion regulation.

This study investigates how integrated bed measurements can be used to assess motor patterns (movements and postures) during sleep. An algorithm has been developed that detects movements based on the time derivate of mattress surface indentation. After each movement, the algorithm recognizes the adopted sleep posture based on an image feature vector and an optimal separating hyperplane constructed with the theory of support vector machines. The developed algorithm has been tested on a dataset of 30 fully recorded nights in a sleep laboratory. Movement detection has been compared to actigraphy, whereas posture recognition has been validated with a manual posture scoring based on video frames and chest orientation. Results show a high sensitivity for movement detection (92.6%) and posture recognition (between 83.6% and 95.9%), indicating that mattress indentation provides an accurate and unobtrusive measure to assess motor patterns during sleep.

Introduction Professionals who are on-call during the night but who are allowed to sleep, report poor qualitative and quantitative sleep. This has detrimental effects on mood and performance the following day. They feel sleepier, are less alert and likely to make errors. This study investigates whether a pre-sleep vigilance inducing instruction impairs the macro- and micro-structure of sleep in healthy volunteers and whether it negatively influences sleep quality, sleepiness and mood the following day. Methods Following an adaptation night 18 subjects (23,89 years +/- 0,78) slept two nights in the sleep laboratory: a reference night and an 'on-call' night in counterbalanced order. In the experimental condition subjects were told five seconds white noise would be presented at unpredictable intervals during the night. Subjects were instructed to press a button at hand as soon as they would hear this noise. In reality no noise was administered during the night. Sleep was recorded polysomnographicaly andevening and morning questionnaires inquired about subjects' sleepiness and mood. Results In comparison to the reference condition subjects felt significantly less fatigue (p

Normal sleep is characterized by the presence of several major posture shifts as well as some smaller body movements that do not necessarily have an effect on sleeping posture.The main ergonomic function of sleeping systems,to provide proper body support,requires the knowledge of the adopted postures throughout the night.This can be achieved by accommodating bedding systems with sensors that measure the deformation of the system due to the human body on top of it.An automatic posture recognition algorithm based on such bed measurements is developed and validated with independent video analysis.The algorithm uses decision rules that are constructed by support vector machines,a kind of learning machine that calculates the optimal separating hyperplane between two classes of a training set of feature vectors.Results are promising with a mean correspondence of 0.92 between automatic and validation posture scorings.Apart from its ergonomic relevance,the developed posture recognition can also serve as a base to compute other motion related parameters that might be relevant to relate to sleep quality.