Translated title of the contribution: The sleep analysis computer (SAC) in the diagnosis of sleep related breathing disorders

B. Hoch, T. Penzel, J. H. Peter, C. Schmid, H. Schneider, P. Von Wichert

Research output: Contribution to journalArticlepeer-review


Sleep related breathing disorders influence the structure of sleep by considerably modifying the ratios of the individual sleep stages. The sleep analyses carried out by polysomnography in the diagnosis of sleep related breathing disorders have so far been evaluated manually according to the criteria of Rechtschaffen and Kales, since automatic systems do not permit standardised evaluation as yet. Automatic sleep analyses via SAC, however, has been developed further in recent years and has widened its scope and efficiency. It is now possible to perform a comprehensive sleep analysis via SAC by means of modified criteria after Rechtschaffen and Kales. The SAC determines individual curves in the EEG and EOG and includes in addition to the EEG parameters an automatic apnoea detection as well as detailed breathing and oxygen saturation analyses. The Sleep Analysis Computer (SAC) records 15 parameters (2 EEG, 2 EOG, 2 EMG, ECG, NAF, thoracic and abdominal breathing curves, oxygen saturation, body posture, optionally blood pressure = RR, CPAP etc.). This means that all the parameters required for diagnosing sleep related breathing disorders as well as their differential diagnosis can be determined. Within the framework of a blood pressure study, 16 patients (average 45.5 SD 4.6 years) were subjected to SAC measurement in addition to conventional PSG. The computer recordings were evaluated according to apnoea index, the form of the apnoea and the oxygen saturation desaturations. The evaluation yielded the following pattern: 4 patients with AI < 10, 8 patients with AI between 10 and 20, 4 patients with AI > 20. Obstructive apnoeas were seen in 6 patients, mixed apnoeas in 8 patients. 2 patients did not show any signal of sleep related breathing disorder. In all patients declines in oxygen saturation > 4% were recorded. SAC enabled definite identification of the different forms of apnoea. The apnoea indices and drops in oxygen saturation corresponded to the results obtained with conventional PSG insofar as the patients could be definitely allocated to the individual apnoea groups (AI < 10, AI 10-20 AI > 20). SAC enables to perform diagnosis on a large scale with the relevant parameters. Validation of the respiratory parameters and of oxygen saturation is at present under way.

Translated title of the contributionThe sleep analysis computer (SAC) in the diagnosis of sleep related breathing disorders
Original languageGerman
Pages (from-to)134-138
Number of pages5
Issue numberSUPPL. 1
StatePublished - 1993
Externally publishedYes

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine


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