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Restorative functions of sleep are of special interest for sleep medicine. For the assessment of these restorative functions, various parameters are taken into account, among which sleep duration and sleep quality play the most important roles. Both terms are essential for sleep perception, expressing the subjective satisfaction of the individual with the time spent asleep. In recent decades, sleep medicine and sleep research have developed methods for the assessment of both objective and subjective dimensions of sleep. Among subjective methods, taking of the medical history focusing on the patient's sleep is important. Standardized and validated questionnaires play a supportive role. Objective methods are, for example, estimation of the sleep-wake cycle by means of actigraphy and polygraphy. Especially in multimorbid patients, polysomnography is still the gold standard method for diagnostics. An important approach during recent years is shifting from bothering overnight examinations into less disturbing procedures for patients that include performing ambulatory, outpatient examinations in the patients' home rather than inpatient surveillance within sleep centers.

Sleep medicine is gaining more and more interest and importance both within medical research and clinical routine. The investigation of sleep and associated disorders requires the overnight acquisition of a huge amount of biosignal data derived from various sensors (polysomnographic recording) as well as consecutive time-consuming manual analysis (polysomnographic analysis). Therefore, the development of automatic analysis systems has become a major focus in sleep research in the recent years, resulting in the development of algorithms for the analysis of different biosignals (EEG, ECG, EMG, breathing signals). In this study, an open source algorithm published by Hamilton et al. was used for ECG analysis, whereas the analysis of breathing signals was done using an algorithm published by Clark et al. using also variations of the intra-thoracic pressure for the detection of breathing disorders. The electromyogram (EMG) analysis was done with a self-made algorithm, whereas EEG analyses are currently under development, using both frequency analysis modules and pattern recognition procedures. Although all these algorithms have proved to be quite useful, their validity and reliability still needs to be verified in future studies. Taking into account that during a standard polysomnographic recording data from approximately 8 hours of sleep are collected, it is imaginable that processing this amount of data by the described algorithms very often exceeds the calculating capacity of current standard computers. Using Grid technology, this limitation can be transcended by splitting biosignal data and distributing it to several analysis computers. Therefore, Grid based automatic analysis systems may improve the effectiveness of polysomnographic investigations and thereby diminish the costs for health care providers.

Background and Objective: Narcolepsy is a rare disease which remains undiagnosed in 90 %. The international literature so far has paid little attention to comorbid disorders., Patients and Methods: In preparation for a German Narcolepsy Register this pilot study evaluated data from hospital records of 106 narcolepsy patients (60 men, 46 women, 8-83 years, mean 45.1 years) retrospectively emphasising comorbid diseases., Results: The parasomnias sleepwalking and nightmares were 6 times as frequent as in the general population. With respect to the HLA findings the extremely high frequency of REM behavior disorder contributes to the assumption of a common pathomechanism. Obstructive sleep apnea and periodic limb movement disorder (PLMD) occurred much less than described in literature, while the results on obesity, headache and depression are in line with published findings., Conclusion: Diagnosis of one of these comorbid disorders should always be followed by thorough investigation for symptoms of narcolepsy i. e. excessive daytime sleepiness, sleep attacks and cataplexy.

The ENN sleep atlas and database was set up on a dedicated server connected to the internet thus providing all services such as WWW, ftp and telnet access. The database serves as a platform to promote the goals of the European Neurological Network, to exchange patient cases for second opinion between experts and to create a case-oriented multimedia sleep atlas with descriptive text, images and video-clips of all known sleep disorders. The sleep atlas consists of a small public and a large private part for members of the consortium. 20 patient cases were collected and presented with educational information similar to published case reports. Case reports are complemented with images, video-clips and biosignal recordings. A Java based viewer for biosignals provided in EDF format was installed in order to move free within the sleep recordings without the need to download the full recording on the client.