Paper Info
Title
Design and Evaluation of an Intelligent Remote Tidal Volume Variability Monitoring System in e-Health Applications
Abstract
A reliable long-term monitoring and diagnosis of breath disorders at an early stage provides an improvement of medical act, life-expectancy and quality of life while decreasing the costs of treatment and medical services. Therefore, a real-time unobtrusive monitoring of respiration patterns, as well as breath parameters is a critical need in medical applications. In this paper, we propose an intelligent system for patient home care, capable of measuring respiration rate and tidal volume variability via a wearable sensing technology. The proposed system is designed particularly for the goal of diagnosis and treatment in patients with pathological breathing e.g. respiratory complications after surgery or sleep disorders. The complete system was comprised of wearable calibrated accelerometer sensor, Bluetooth Low Energy (BLE) and cloud database. The experiments are conducted with 8 subjects and the overall error in respiration rate calculation is obtained 0.29%±0.33% considering SPR-BTA spirometer as the reference. We also introduce a method for Tidal Volume variability (TVvar) estimation while validated using Pearson correlation. Furthermore, since it is essential to detect the critical events resulted from sudden rise or fall in per breath tidal volume of the patients, we provide a technique to automatically find the accurate threshold values based on each individual breath characteristics. Therefore, the system is able to detect the major changes, precisely by more than 98% and provide immediate feedback such as sound alarm for round-the-clock respiration monitoring.
Year
DOI
Venue
2015
10.1109/JBHI.2015.2445783
IEEE J. Biomedical and Health Informatics
Keywords
Field
DocType
Alarm system,breath disorders,medical application,remote monitoring,respiration,tidal volume
Telemedicine,Spirometer,Tidal volume,Simulation,ALARM,Computer science,Wearable computer,Accelerometer,Breathing,Cloud database
Journal
Volume
Issue
ISSN
PP
99
2168-2194
Citations 
PageRank 
References 
8
0.64
17
Authors
3
Name
Order
Citations
PageRank
Fekr, A.Roshan1302.77
Katarzyna Radecka280.64
Zeljko Zilic3312.96