Paper Info
Title
BreathEasy: Assessing Respiratory Diseases Using Mobile Multimodal Sensors
Abstract
Mobil respiratory assessments using commodity smartphones and smartwatches are unmet needs for patient monitoring at home. In this paper, we show the feasibility of using multimodal sensors embedded in consumer mobile devices for non-invasive, low-effort respiratory assessment. We have conducted studies with 228 chronic respiratory patients and healthy subjects, and show that our model can estimate respiratory rate with mean absolute error (MAE) 0.72$\pm$0.62 breath per minute and differentiate respiratory patients from healthy subjects with 90% recall and 76% precision when the user breathes normally by holding the device on the chest or the abdomen for a minute. Holding the device on the chest or abdomen needs significantly lower effort compared to traditional spirometry which requires a specialized device and forceful vigorous breathing. This paper shows the feasibility of developing a low-effort respiratory assessment towards making it available anywhere, anytime through users' own mobile devices.
Year
DOI
Venue
2020
10.1145/3382507.3418852
ICMI '20: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION Virtual Event Netherlands October, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7581-8
0
PageRank 
References 
Authors
0.34
0
10
Name
Order
Citations
PageRank
Md. Mahmudur Rahman11716.00
Mohsin Yusuf Ahmed200.34
Tousif Ahmed3326.26
Bashima Islam4152.54
Viswam Nathan55014.09
Korosh Vatanparvar613416.20
Ebrahim Nemati78415.30
Daniel McCaffrey810.69
Jilong Kuang93817.00
Jun Alex Gao1022.42