Paper Info
Title
Assessing Severity of Pulmonary Obstruction from Respiration Phase-Based Wheeze-Sensing Using Mobile Sensors
Abstract
Obstructive pulmonary diseases cause limited airflow from the lung and severely affect patients' quality of life. Wheeze is one of the most prominent symptoms for them. High requirements imposed by traditional diagnosis methods make regular monitoring of pulmonary obstruction challenging, which hinders the opportunity of early intervention and prevention of significant exacerbation. In this work, we explore the feasibility of developing a mobile sensor-based system as a convenient means of assessing the severity of pulmonary obstruction via respiration phase-based symptomatic wheeze sensing. We conduct a 131 subjects' (91 patients and 40 healthy) study for the detection (F1: 87.96%) and characterization (F1: 79.47%) of wheeze. Subsequently, we develop novel wheeze metrics, which show a significant correlation (Pearson's correlation: -0.22, p-value: 0.024) with standard spirometry measure of pulmonary obstruction severity. This work takes a principal step towards the unobtrusive assessment of pulmonary condition from mobile sensor interactions.
Year
DOI
Venue
2020
10.1145/3313831.3376444
CHI '20: CHI Conference on Human Factors in Computing Systems Honolulu HI USA April, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-6708-0
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Soujanya Chatterjee1293.79
Md. Mahmudur Rahman21716.00
Tousif Ahmed3326.26
Nazir Saleheen4477.07
Ebrahim Nemati58415.30
Viswam Nathan65014.09
Korosh Vatanparvar713416.20
Jilong Kuang83817.00