Title
Periodic Breathing During Ascent To Extreme Altitude Quantified By Spectral Analysis Of The Respiratory Volume Signal
Abstract
High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1st and 2nd ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.
Year
DOI
Venue
2012
10.1109/EMBC.2012.6346029
2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
Field
DocType
sensitivity analysis,cardiology,plethysmography,sleep
Sleep apnea,Respiratory minute volume,Computer science,Artificial intelligence,Respiratory system,Computer vision,Effects of high altitude on humans,Simulation,Internal medicine,Cardiology,Altitude,Control of respiration,Cheyne–Stokes respiration,Periodic breathing
Conference
Volume
ISSN
Citations 
2012
1557-170X
1
PageRank 
References 
Authors
0.47
1
14
Name
Order
Citations
PageRank
Ainara Garde15612.88
B F Giraldo210.47
R Jané313143.71
T D Latshang410.47
A J Turk510.47
T Hess610.47
M M Bosch710.47
D Barthelmes810.47
J Pichler Hefti910.47
M Maggiorini1010.47
U Hefti1110.47
T M Merz1210.47
O D Schoch1310.47
K E Bloch1410.47