eISSN: 2618-6446
Conferences Latest Issue Archive Future Issues About Us Journals

SETSCI - Volume 1 (2017)
ISMSIT2017 - International Symposium on Multidisciplinary Studies and Innovative Technologies, Tokat, Turkey, Dec 02, 2017

Detection of Apnea Event with ANN Using Acceleration Data (ISMSIT2017_50)
Harun Sümbül1*, A. Hayrettin Yüzer2
1Ondokuz Mayis University, Samsun, Turkey
2Karabuk University, Karabük, Turkey
* Corresponding author: harun.sumbul@omu.edu.tr
Published Date: 2017-12-08   |   Page (s): 219-221   |    87     0

ABSTRACT In this study, the accelerations caused by the diaphragm movements during respiration were monitored with a 3-axis accelerometer and the measured accelerations were recorded on an SD card. A measurement system for this purpose was developed. The moments in which diaphragm movements stopped were detected by using Matlab. An ANN has been designed to simulate measured real data. A total of 5886 real data were applied to ANN. In the training of ANN, 3943 randomly selected from these data (66.6% of the total data) were used. The remaining 1943 data (33.33% of the total data) was also used for the test. Thereby estimating the apnea event was provided by the designed ANN. The results were plotted and proved to be quite similar to each other.As a result, apnea events have been successfully detected.
KEYWORDS Apnea event, accelerometer, ANN, microprocessor.
REFERENCES [1] B. Xie, H. Minn, “Real-Time Sleep Apnea Detection by Classifier Combination,” IEEE Transactions On Information Technology In Biomedicine 2012; 16: 3:469-477.

[2] P. Várady, T. Micsik, S. Benedek, Z. Benyó, “A Novel Method for the Detection of Apnea and Hypopnea Events in Respiration Signals,” IEEE Transactions On Biomedical Engineering 2002; 49: 9: 936-942.

[3] G. Cetintas, “Apne-hipopne indeksi ile akciğer volümleri ve hava yolu rezistansı arasındaki ilişkinin tanımlanması,” T.C. Sağlık Bakanlığı Süreyyapaşa Göğüs Hastalıkları Ve Göğüs Cerrahisi E.A. Hastanesi, İstanbul, Türkiye, 2008.

[4] M.E.Tagluk, M. Akin, N. Sezgin, “Classification of sleep apnea by using wavelet transform and artificial neural networks,” Expert Systems with Applications 2010; 37:2:1600-1607.

[5] S.F. Güven, “Solunum Kayıtlarının Skorlanması,” Eurasian J Pulmonol 2013; 15: 30-34.

[6] M. A. S. Serdaroğlu, "A measurement system for human movement analysis," Master of Science Thesis, Department of Signals and System Division of Biomedical Engineering Chalmers Unıversity Of Technology, Göteborg, Sweden, (2011).

[7] J. Ning, “Detecting human falls with a 3-axis digital accelerometer,” Analog Dialogue 2009:43-07, [Online]. Available: http://www.analog.com/library/analogdialogue/archives/43-07/fall_detector.html, access date: 11/08/2017, time: 11:51.

[8] Sümbül, H., Yüzer A. H., “Development of diagnostic device for COPD: A Mems based approach, “ IJCSNS International Journal of Computer Science and Network Security, Vol:17, No:7, pp. 196-203,July 2017.

[9] Sümbül, H., Yüzer A. H.,“3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome”, Journal of New Results in Science, vol. 12, no. 2016, pp. 59–70, Nov. 2016. ISSN:1304-7981.

[10] Sümbül, H., “Uyku apnesi ve koah hastaliklari için tani yöntemi geliştirilmesi,” Ph. D. Thesis, Karabuk University Graduate School of Natural and Applied Sciences Department of Electrical-Electronics Engineering, Karabuk, Turkey, September 2017.

[11] I. Saritas, I. A. Ozkan and I. U. Sert, "Prognosis of prostate cancer by artificial neural networks", Expert Systems with Applications, 37(9):6646-6650 (2010).

[12] I. A. Ozkan, S. Herdem, I. Saritas, "FPGA-based self-organizing fuzzy controller for electromagnetic filter", Neural Computing and Applications, 28(9): 2535-2543 (2017).

SET Technology - Turkey

eISSN  : 2618-6446

E-mail : info@set-science.com
+90 533 2245325

Tokat Technology Development Zone Gaziosmanpaşa University Taşlıçiftlik Campus, 60240 TOKAT-TURKEY
©2018 SET Technology