Computer Supported Detection for Obstructive Sleep Apnea Using Electrocardiographic-Acceleration Sensors

Chang Man Kim; Ji Won Baek; Yoon Nyun Kim; Hyung Jin Kim; Tea Hyung Kim; Sang Hee Kim; Jong Ha Lee

doi:10.4028/www.scientific.net/AMM.556-562.2715

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Computer Supported Detection for Obstructive Sleep...

Computer Supported Detection for Obstructive Sleep Apnea Using Electrocardiographic-Acceleration Sensors

Abstract:

Obstructive sleep apnea syndrome is a sleep-related breathing disorder that is caused by obstruction of the upper airway. 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. 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.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

2715-2718

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.2715

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Online since:

May 2014

Authors:

Chang Man Kim, Ji Won Baek, Yoon Nyun Kim, Hyung Jin Kim, Tea Hyung Kim, Sang Hee Kim*, Jong Ha Lee

Keywords:

Acceleration Sensor, Adaboost, Computer Aided Diagnosis, Electrocardiography, Machine Learning, Obstructive Sleep Apnea

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* - Corresponding Author

References

[1] I. Kim. A study on woman's sleep disorder and depression, Ph.D. dissertation, EwhaWomans University.

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