scholarly journals Using the Entropy of Tracheal Sounds to Detect Apnea during Sedation in Healthy Nonobese Volunteers

2013 ◽  
Vol 118 (6) ◽  
pp. 1341-1349 ◽  
Author(s):  
Lu Yu ◽  
Chien-Kun Ting ◽  
Bryce E. Hill ◽  
Joseph A. Orr ◽  
Lara M. Brewer ◽  
...  

Abstract Background: Undetected apnea can lead to severe hypoxia, bradycardia, and cardiac arrest. Tracheal sounds entropy has been proved to be a robust method for estimating respiratory flow, thus maybe a more reliable way to detect obstructive and central apnea during sedation. Methods: A secondary analysis of a previous pharmacodynamics study was conducted. Twenty volunteers received propofol and remifentinal until they became unresponsive to the insertion of a bougie into the esophagus. Respiratory flow rate and tracheal sounds were recorded using a pneumotachometer and a microphone. The logarithm of the tracheal sound Shannon entropy (Log-E) was calculated to estimate flow rate. An adaptive Log-E threshold was used to distinguish between the presence of normal breath and apnea. Apnea detected from tracheal sounds was compared to the apnea detected from respiratory flow rate. Results: The volunteers stopped breathing for 15 s or longer (apnea) 322 times during the 12.9-h study. Apnea was correctly detected 310 times from both the tracheal sounds and the respiratory flow. Periods of apnea were not detected by the tracheal sounds 12 times. The absence of tracheal sounds was falsely detected as apnea 89 times. Normal breathing was detected correctly 1,196 times. The acoustic method detected obstructive and central apnea in sedated volunteers with 95% sensitivity and 92% specificity. Conclusions: We found that the entropy of the acoustic signal from a microphone placed over the trachea may reliably provide an early warning of the onset of obstructive and central apnea in volunteers under sedation.

1975 ◽  
Vol 39 (2) ◽  
pp. 305-311 ◽  
Author(s):  
D. C. Stanescu ◽  
R. Fesler ◽  
C. Veriter ◽  
A. Fans ◽  
L. Brasseur

We have modified the measurements of the resistance of the respiratory system, Rrs, by the forced oscillation technique and we have developed equipment to automatically compute Rrs. Flow rate and mouth pressure are treated by selective averaging filters that remove the interference of the subject's respiratory flow on the imposed oscillations. The filtered mean Rrs represents a weighted ensemble average computer over both inspiration and expiration. This method avoids aberrant Rrs values, decreases the variability, and yields an unbiased mean Rrs. Rrs may be measured during slow or rapid spontaneous breathing, in normals and in obstructive patients, over a range of 3–9 Hz. A good reproducibility of Rrs at several days' interval was demonstrated. Frequency dependence of Rrs was found in patients with obstructive lung disease but not in healthy nonsmokers.


2010 ◽  
Vol 31 (3) ◽  
pp. 427-438 ◽  
Author(s):  
A Kulkas ◽  
E Huupponen ◽  
J Virkkala ◽  
A Saastamoinen ◽  
E Rauhala ◽  
...  

2012 ◽  
Vol 57 (SI-1 Track-L) ◽  
Author(s):  
K. A. Sohrabi ◽  
D. Basu ◽  
F. Schudt ◽  
M. Scholtes ◽  
O. Seifert ◽  
...  

2020 ◽  
Vol 10 (6) ◽  
pp. 2335-2347
Author(s):  
Ehsan Khamehchi ◽  
Mohammad Zolfagharroshan ◽  
Mohammad Reza Mahdiani

Sign in / Sign up

Export Citation Format

Share Document