NDLI: Acoustic Monitoring of Lung Sounds for the Detection of One Lung Intubation

Content Provider	IEEE Xplore Digital Library
Author	Tejman-Yarden, S. Zlotnik, A. Weizman, L. Gurman, G.M. Tabrikian, J.
Copyright Year	2006
Description	Author affiliation: Div. of Pediatrics, Soroka Med. Center, Beer-Sheva (Tejman-Yarden, S.)
Abstract	One lung intubation (OLI) is a major incident during endotracheal intubation. Monitoring methods used today have been found to be non specific and controversial regarding its early diagnosis. We have developed a new system which detects OLI based on electronic lung sounds analysis during artificial ventilation. 24 adult surgical patients schedualed for routine surgical procedures were included. Lung sound sampling was done during induction to anesthesia and tube positioning by four piezoelectric microphones attached to the patients' back. To achieve OLI, the endotracheal tube was inserted and advanced down the airway so that no left breath sounds were heard; the tube was then withdrawn stepwise until equal breath sounds could be heard. The final position of the tube was confirmed by fiberoptic bronchoscopy. The sampled lung sound were processed by an algorithm which assumes a MIMO (multi input multi output) system; in which a multi-dimensional auto-regressive (AR) model relates the input (lungs) and the output (recorded sounds). A detector for OLI was developed, based on a generalized likelihood ratio test, which was implemented under a coherent sources assumption. Based on this new algorithm the probability of OLI detection is 95.2% with a probability of 4.8% false alarm. We can assume even higher values of detection, depending on the sensitivity wanted, taking in mind higher incidence of false alarms. We present a new device, already in prototype, which detects OLI in various clinical scenarios with a very high degree of accuracy.
Starting Page	186
Ending Page	186
File Size	106372
Page Count	1
File Format	PDF
ISBN	142440858X
DOI	10.1109/ITRE.2006.381560
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-16
Publisher Place	Israel
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lungs Acoustic signal detection Surgery Patient monitoring Ventilation Sampling methods Anesthesia Microphones Optical fiber testing Bronchoscopy
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Monitoring of separate lung ventilation in anesthesia and intensive care

Detection of one lung intubation by monitoring lungs sounds

Detection of Breathing

Flow And Volume Related AR-modelling Of Lung Sounds

Revisiting the video stethoscope: An application of digital signal processing software (Goldwave ®) to monitoring ventilation in intubated patients

Classification between normal and abnormal respiratory sounds based on maximum likelihood approach

Design, construction, and evaluation of a bioacoustic transducer testing (BATT) system for respiratory sounds

Acoustical signal properties for cardiac/respiratory activity and apneas

Acoustic monitoring of double-lumen ventilated lungs for the detection of selective unilateral lung ventilation.

Acoustic Monitoring of Lung Sounds for the Detection of One Lung Intubation

Similar Documents

Monitoring of separate lung ventilation in anesthesia and intensive care

Detection of one lung intubation by monitoring lungs sounds

Detection of Breathing

Flow And Volume Related AR-modelling Of Lung Sounds

Revisiting the video stethoscope: An application of digital signal processing software (Goldwave ®) to monitoring ventilation in intubated patients

Classification between normal and abnormal respiratory sounds based on maximum likelihood approach

Design, construction, and evaluation of a bioacoustic transducer testing (BATT) system for respiratory sounds

Acoustical signal properties for cardiac/respiratory activity and apneas

Acoustic monitoring of double-lumen ventilated lungs for the detection of selective unilateral lung ventilation.

Acoustic Monitoring of Lung Sounds for the Detection of One Lung Intubation