Document Detail

Detection of respiration in central venous pressure using state machine.
MedLine Citation:
PMID:  24110572     Owner:  NLM     Status:  Publisher    
Reliable information from patient monitors enhances treatment for critically ill patients. Redundant sources for information would aid identification of faulty sensors and leads, and improve presentation of physiological data. Respiratory information can be obtained from several sources, including airway pressure and central venous pressure (CVP). CVP signals have been analyzed using frequency information to isolate the respiration related part of the signal or to obtain statistics about respiration. This study uses a state machine algorithm to detect the timing of each cycle of respiration. A state machine has advantages of enforcing a predictable cycle of expiration and inspiration. The detection of respiratory cycles can be done in real-time, allowing identification of irregular periods between inspirations and prolonged periods with no inspiration, for which an alert may be issued. The algorithm was tested on data obtain from the PhysioNet database of recordings from intensive care patients. The airway pressure signal was used to determine the "true values" of the timing of each respiratory cycle for checking the accuracy of the algorithm analyzing the CVP signal. Parameters of the algorithm were found that would result in a true positive value of above 98% for detection of each cycle of respiration from analysis of the CVP signal, compared to analysis of the RESP signal.
Douglas E Dow; Alejandra P Garcia
Publication Detail:
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference     Volume:  2013     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2013 Jul 
Date Detail:
Created Date:  2013-10-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  -    
Other Details:
Languages:  ENG     Pagination:  3853-3856     Citation Subset:  -    
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