Open AccessHeart Rate Variability Analysis Assessment for Asthma Control Stratification
Author(s) -
Javier Milagro,
Lorena Soto,
Jordi Giner,
Carolina Varon,
Pablo Laguna,
Vicente Plaza,
Eduardo Gil,
Raquel Bailon
Publication year - 2020
Publication title -
2019 computing in cardiology (cinc)
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.257
H-Index - 55
ISSN - 2325-887X
ISBN - 978-1-7281-6936-1
DOI - 10.22489/cinc.2019.075
Subject(s) - bioengineering , computing and processing , signal processing and analysis
Autonomic nervous system (ANS) has been suggested to play a major role in the pathogenesis of asthma. This hypothesis has motivated large research, revealing a reduced modulation of the heart rate in subjects with uncontrolled asthma, when compared to asthmatics with controlled symptomatology. In this work, we assessed ANS activity through heart rate variability analysis in a group of asthmatics classified attending to the control of their symptoms. This information was later used for training a logistic regression classifier aiming at differentiating between the levels of control in asthmatic patients. The accuracy of the classifier improved when including ANS information (71.77%, versus 64.73% when only clinical parameters were considered), suggesting that ANS assessment could contribute to better non-invasive asthma monitoring.