Paper Info
Title
Respiratory Frequency Estimation From Accelerometric Signals Acquired By Mobile Phone In A Controlled Breathing Protocol
Abstract
The aim of this work was to test if the smartphone's embedded triaxial accelerometer can be used to extract respiratory frequency information from the chest movements during a controlled breathing protocol. Respiratory signals from 10 young volunteers were recorded simultaneously, by two smartphones (iPhone 4s and 6s; sampling frequency similar to 100 Hz), positioned one on the sternum and one on the belly, while in supine posture. At the same time, a belt transducer was used to acquire the reference respiratory signal. A controlled breathing protocol, consisting of four consecutive phases of 12 respiratory cycles each (respiratory frequencies at 0.25, 0.17, 0.125 and 0.1 Hz), was imposed through the visualization of a moving bar on a display. After low-pass filtering (fc=0.5 Hz), the respiratory signal was obtained from both smartphones, and respiratory frequency derived for each phase. Compared to the belt transducer, the resulting error was lower than 2% for each imposed respiratory frequency, for both smartphones' positions, with better results obtained for the smartphone positioned above the belly.
Year
DOI
Venue
2017
10.22489/CinC.2017.137-402
2017 COMPUTING IN CARDIOLOGY (CINC)
Field
DocType
Volume
Transducer,Accelerometer,Computer science,Sampling (signal processing),Filter (signal processing),Respiratory system,Breathing,Mobile phone,Acoustics,Supine position
Conference
44
ISSN
Citations 
PageRank 
2325-8861
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
Federica Landreani100.68
Alba Martín200.34
Claudia Casellato3288.64
Esteban Pavan400.34
Carlo A. Frigo501.35
P-F Migeotte662.83
Andrea Faini73110.45
Gianfranco Parati83910.27
E G Caiani9810.73