Title
Monitoring obstructive sleep apnea with electrocardiography and 3-axis acceleration sensor
Abstract
Obstructive sleep apnea syndrome is a sleep-related breathing disorder that is caused by obstruction of the upper airway. This condition may be related with many clinical sequelae such as cardiovascular disease, high blood pressure, stroke, diabetes, and clinical depression. To diagnosis obstructive sleep apnea, in-laboratory full polysomnography is considered as a standard test to determine the severity of respiratory disturbance. However, polysomnography is expensive and complicated to perform. In this research, we explore a computer-aided diagnosis system with portable ECG equipment and tri-accelerometer (x, y, and z-axes) that can automatically analyze biosignals and test for OSA. Traditional approaches to sleep apnea data analysis have been criticized;however, there are not enough suggestions to resolve the existing problems. As an effort to resolve this issue, we developed an approach to record ECG signals and abdominal movements induced by breathing by affixing ECG-enabled electrodes onto a triaxial accelerometer. With the two signals simultaneously measured, the apnea data obtained would be more accurate, relative to cases where a single signal is measured. This would be helpful in diagnosing OSA. Moreover, a useful feature point can be extracted from the two signals after applying a signal processing algorithm, and the extracted feature point can be applied indesigning a computer-aided diagnosis algorithm using a machine learning technique.
Year
DOI
Venue
2015
10.1145/2769493.2769522
International Conference on Pervasive Technologies Related to Assistive Environments
Keywords
Field
DocType
Computer-aided diagnosis, obstructive sleep apnea, acceleration sensor, electrocardiography, Adaboost, machine learning
Obstructive sleep apnea,Sleep apnea,Computer science,Accelerometer,Simulation,Computer-aided diagnosis,Apnea,Breathing,Physical medicine and rehabilitation,Electrocardiography,Polysomnography
Conference
Citations 
PageRank 
References 
1
0.38
0
Authors
3
Name
Order
Citations
PageRank
Jong-Ha Lee112.07
Hee-Jun Park220.75
Yoon Nyun Kim371.59