Abstract
Sleep apnea diagnosis is traditionally being
made by a medical device called polysomnography (PSG). People have to sleep in
specific sleep laboratories and PSG monitors 14 different parameters for result
evaluations. Due to difficulties of this customary method for the restricted
and elder people, a novel Decision Support Software (DSS), which can help
doctors in deciding whether that type of people require further investigation
with PSG in sleep laboratories or not, is developed in this research. The only
parameter that is being focused in the developed DSS is the oxygen saturation
(SpO2) since it is related with respiration and it can be easily measured from
the finger without ruining the sleep comfort. The PSG results of 100 subjects from
Sleep Heart Health (SHH) data set of the National Sleep Research Resource
(NSRR) are uploaded to Microsoft
Structured Query Language (MS SQL) database server system and analyzed by the DSS
designed with MS SQL. As a consequence, DSS and NSRR sleep apnea outputs match
with a ratio of 76 % for “non-risk for sleep apnea” status. This result shows that
DSS has a potential in supporting decisions of medical doctors about
sleep apnea diagnosis.
References
- 1. Almazaydeh, L., Elleithy, K., and Faezipour M. (2014) A highly Reliable and Fully Automated Classification System for Sleep Apnea Detection, International Journal of Intelligent Systems and Applications in Engineering, 4(3), 66-70 doi: 10.18201/ijisae.47487
- 2. Berry, R. B. , Wagner, Mary H. (2015) Sleep Medicine Pearls (Third Edition), Elsevier, Philadelphia.
- 3. Foroughi, M. , Razavi, H., Malekmohammad, M., Naghan, P.A., Jamaati, H.(2016) Diagnosis of Obstructive Sleep Apnea Syndrome in Adults: A Brief Review of Existing Data for Practice in Iran, National Research Institute of Tuberculosis and Lung Disease, Iran, 15(2): 70-74
- 4. http://healthysleep.med.harvard.edu/sleep-apnea/diagnosing-osa/understanding-results, Erişim Tarihi: 31.03.2019, Konu: Understanding the Results
- 5. https://www.sleepdata.org/datasets/, Erişim Tarihi: 31.03.2019, Konu: Datasets
- 6. https://www.sleepdata.org/datasets/shhs/pages/08-equipment-shhs1.md, Erişim Tarihi: 31.03.2019, Konu: Technical Notes on SHHS1.
- 7. https://sleepdata.org/datasets/shhs/variables , Erişim Tarihi: 08.05.2019, Konu: Overview
- 8. Köktürk, O. (1998) Uykuda solunum bozuklukları; tarihçe, tanımlar, hastalık spektrumu ve boyutu. Tüberküloz ve Toraks Dergisi, 46(2), 182- 187.
- 9. Kushida, CA. , Littner, MR and Morgenthaler T. (2005) Practice parameters for the indications for polysomnography and related procedures: an update for 2005, PubMED, 28, 499-521.
- 10. Numanoğlu, N. , Acıcan, T. ve Ur, Ö. (1997) Uyku apnesi sendromu. In:Numanoğlu N(ed) Solunum Sistemi ve Hastalıkları. Antıp, 468-476.
- 11. Sateia, M. J, (2014) International Classification of Sleep Disorders (ICSD), 3rd ed, American Academy of Sleep Medicine, Illinois.
Abstract
tanısı, geleneksel olarak bireylerin uyku laboratuvarlarında polisomnografi
(PSG) cihazına bağlanması ve uyku süresi boyunca izlenen 14 farklı parametre
ile ilgili ölçümlerin değerlendirilmesi sonucunda konulmaktadır. Ancak bu durum, hareket kısıtlamalı ve yaşlı
kişiler için önemli zorluklar oluşturmaktadır. Bu çalışmada, belirtilen tipteki
kişilerin ileri tetkikler için hastanedeki uyku laboratuvarlarına gelmelerinin
gerekli olup olmadığı kararının verilmesi konusunda hekimlere yardımcı
olabilecek bir karar destek yazılımı (KDY) geliştirilmiştir. KDY’de ilgilenilen
parametre, sadece kandaki oksijen satürasyonudur (SpO2). SpO2’nin seçilme
sebebi, solunumla ilgili olması ve parmağa takılan bir cihazla kolaylıkla
ölçülebilmesi nedeniyle kişinin uyku konforunu bozmamasıdır. Amerikan Ulusal Uyku Araştırmaları Kaynağı’na
(National Sleep Research Resource, NSRR) ait Uyku Kalp Sağlığı (Sleep Heart
Health, SHH) veri setindeki 100 denekten alınan PSG cihazı çıktıları, Microsoft Structured Query Language (MS SQL)
veri tabanı sunucusuna aktarılmış ve MS SQL kullanılarak tasarlanan KDY
ile incelenmiştir. Bu inceleme sonucunda, “uyku apnesi riski yok” tespitinde,
KDY’nin NSRR ile % 76 düzeylerinde eşleşme oranlarına sahip olduğu görülmüştür.
Bu sonuç, geliştirilen KDY’de, hekim kararlarını destekleme potansiyeli bulunduğunu
göstermektedir.
References
- 1. Almazaydeh, L., Elleithy, K., and Faezipour M. (2014) A highly Reliable and Fully Automated Classification System for Sleep Apnea Detection, International Journal of Intelligent Systems and Applications in Engineering, 4(3), 66-70 doi: 10.18201/ijisae.47487
- 2. Berry, R. B. , Wagner, Mary H. (2015) Sleep Medicine Pearls (Third Edition), Elsevier, Philadelphia.
- 3. Foroughi, M. , Razavi, H., Malekmohammad, M., Naghan, P.A., Jamaati, H.(2016) Diagnosis of Obstructive Sleep Apnea Syndrome in Adults: A Brief Review of Existing Data for Practice in Iran, National Research Institute of Tuberculosis and Lung Disease, Iran, 15(2): 70-74
- 4. http://healthysleep.med.harvard.edu/sleep-apnea/diagnosing-osa/understanding-results, Erişim Tarihi: 31.03.2019, Konu: Understanding the Results
- 5. https://www.sleepdata.org/datasets/, Erişim Tarihi: 31.03.2019, Konu: Datasets
- 6. https://www.sleepdata.org/datasets/shhs/pages/08-equipment-shhs1.md, Erişim Tarihi: 31.03.2019, Konu: Technical Notes on SHHS1.
- 7. https://sleepdata.org/datasets/shhs/variables , Erişim Tarihi: 08.05.2019, Konu: Overview
- 8. Köktürk, O. (1998) Uykuda solunum bozuklukları; tarihçe, tanımlar, hastalık spektrumu ve boyutu. Tüberküloz ve Toraks Dergisi, 46(2), 182- 187.
- 9. Kushida, CA. , Littner, MR and Morgenthaler T. (2005) Practice parameters for the indications for polysomnography and related procedures: an update for 2005, PubMED, 28, 499-521.
- 10. Numanoğlu, N. , Acıcan, T. ve Ur, Ö. (1997) Uyku apnesi sendromu. In:Numanoğlu N(ed) Solunum Sistemi ve Hastalıkları. Antıp, 468-476.
- 11. Sateia, M. J, (2014) International Classification of Sleep Disorders (ICSD), 3rd ed, American Academy of Sleep Medicine, Illinois.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | August 30, 2019 |
| Submission Date | April 5, 2019 |
| Acceptance Date | June 3, 2019 |
| Published in Issue | Year 2019 Volume: 24 Issue: 2 |
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