• [A computerized processing uni...

Treffer: [A computerized processing unit for ambulatory diagnosis of sleep apnea and nocturnal hypoxemia].

Title:
[A computerized processing unit for ambulatory diagnosis of sleep apnea and nocturnal hypoxemia].
Transliterated Title:
Computerisierte Erfassungseinheit zur ambulanten Diagnostik von Schlaf-Apnoe und nächtlicher Hypoxämie.
Authors:
Hamm M; Abteilung Pneumologie der Medizinischen Hochschule, Hannover., Krause J, Felsmann M, Barnstorf D, Kothe R, Fabel H
Source:
Pneumologie (Stuttgart, Germany) [Pneumologie] 1990 Feb; Vol. 44 Suppl 1, pp. 627-8.
Publication Type:
Journal Article
Language:
German
Journal Info:
Publisher: Thieme Country of Publication: Germany NLM ID: 8906641 Publication Model: Print Cited Medium: Print ISSN: 0934-8387 (Print) Linking ISSN: 09348387 NLM ISO Abbreviation: Pneumologie Subsets: MEDLINE
Imprint Name(s):
Original Publication: Stuttgart ; New York : Thieme, [c1989-
MeSH Terms:
Microcomputers* , Signal Processing, Computer-Assisted*, Circadian Rhythm/*physiology , Diagnosis, Computer-Assisted/*instrumentation , Hypoxia/*diagnosis , Monitoring, Physiologic/*instrumentation , Sleep Apnea Syndromes/*diagnosis, Algorithms ; Electrocardiography/instrumentation ; Humans ; Oximetry/instrumentation ; Respiratory Function Tests/instrumentation
Entry Date(s):
Date Created: 19900201 Date Completed: 19900814 Latest Revision: 20161123
Update Code:
20250114
PMID:
2195533
Database:
MEDLINE

Weitere Informationen

A new mobile device for the evaluation of the sleep-apnoea-syndrome in outpatients prior to conventional polysomnography, processes and stores the oronasal airflow detected by a thermistor, and the heart rate and oxygen saturation in a microprocessor unit. The major problem in on-line data processing of these variables is the interpretation of the thermistor signal for correct apnoea detection. This preliminary study investigates the reliability of the computer algorithm by control of the automatic airflow assessment. With a sensitivity of 97.3% the algorithm proved to be extreme reliable. Combined with the detection of heart rate and oxygen saturation it provides the capacity for comprehensive analysis of cardiorespiratory events and appears to be suitable for application in an outpatient setting.