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Breathing Pattern Estimation Using Wearable Bioimpedance for Assessing COPD Severity

delete2022-12-01
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OA
AI
D
Dolores Blanco-Almazán *
W
Willemijn Groenendaal
L
Lien Lijnen
R
Rana Onder
C
C. J. P. P. Smeets
D
David Ruttens
F
Francky Catthoor
R
R. Jané
DOI:10.1109/JBHI.2022.3207416delete
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摘要

摘要

En 中文
Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.
Keyword:
Bioimpedance
chronic obstructive pulmonary disease
6MWT
breathing pattern
wearables

期刊

IEEE Journal of Biomedical and Health Informatics 封面图
IEEE Journal of Biomedical and Health Informatics
IF:
6.8
论文数:
4.7K
被引数:
2.0W

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E
east limburg hospital
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1.0K
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C
ciberbbn
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1.8K
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university of barcelona
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C
ciber - centro de investigacion biomedica en red
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3.5W
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U
universitat politecnica de catalunya
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1.9W
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被引数: 17
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