Abstract
Dünyada ve
ülkemizde ölümle sonuçlanan vakaların başında kardiyak aciller yer almaktadır.
Kardiyak acillerde zamanında ve etkin acil bakım uygulayabilmek çok önemlidir.
Kalp hastalıkları en kısa sürede tanımlanabilmeli, tedaviye yönelik çalışmalar
başlatılmalı ve en yakın sağlık merkezi ile koordinasyon sağlanıp sevkiyatı
yapılmalıdır. Bu çalışmada kalp rahatsızlığı olan kişilerin uzaktan takibi için
hasta, doktor ve sağlık merkezini kapsayan akıllı bir bilgi sistemi oluşturulmuş
ve oluşabilecek herhangi bir anomali durumunda hasta, yakınları, doktor ve
ilgili sağlık merkezlerinin erken uyarı amaçlı bilgilendirilmesi sağlanmıştır.
Bu kapsamda kalp hastalıklarının tanımlanması sürecinde yoğun kullanılan
parametrelerin ölçümü için donanımsal bileşenler EKG cihazı, nabız ölçer ve
tansiyon ölçer gibi cihazlardır. Bu bağlamda mevcut çalışmada nabız ölçer
cihazı donanımsal ve yazılımsal olarak gerçekleştirilmiştir. Hasta kayıtları
için esneklik, ölçeklenebilirlik, performans/fiyat avantajları yanında mobil ve
web ortamını tek merkezden kullanmak ve yönetmek için avantajlar sağlayan
merkezi bulut sistemi kullanılmıştır. Hastadan elde edilen nabız verileri bulut
sistemine hastanın geçmiş kayıtları olarak kayıt edilmiş ve analiz edilmiştir.
Bu analizler sonucunda acil durumların otomatik olarak sistem tarafından
tespiti ve ilgili yerlere bildirimi gerçekleştirilmiştir.
References
- Akansu A.N., Serdjin W.A., and Selesnick, (2010). Wavelet Transforms in Signal Processing: A Review of Emerging Applications, Physical Communication, Elsevier, vol:3, issue 1, pp. 1-18. (Ulusal - Uluslararası Makale)
- Ambekar M.R., Prabhu S., (2015). A Novel Algorithm to Obtain Respiratory Rate from the PPG Signal. International Journal of Computer Applications. Vol: 126.
- Bruylants T., Munteanu A, Schelkens P.,(2015). Wavelet based volumetric medical image compression, Signal Processing: Image Communication, Vol. 31, pp. 112-133.
- Çetinkaya A., (2014). http://www.minepla.net/2014/08/wcf-ile- asp-net-web-api-nedir (Web Adresleri)
- Gavrylyuk K., (2016). https://azure.microsoft.com/en-us/documentation/articles/ app-service-mobile-value-prop (Web Adresleri)
- Grover L, (1996). A Fast Quantum Mechanical Algorithm for Database Search. Proceedings of the 28th Annual ACM Symposium on the Theory of Computing, pp.212-219.
- Gül F.T., Akif K.(2012) Giyilebilir EKG Uygulaması ve Kullanılabilir Kablosuz İletişim Teknolojilerinin Karşılaştırılması, Akademik Bilişim 2012
- I. Daubechies, (1988). Orthonormal bases of compactly supported wavelets, Comm. Pure Appl. Math. 909996.
- Jui-chien Hsieh, Meng-Wei Hsu (2012) A cloud computing based 12-lead ECG telemedicine service. BMC Medical Informatics and Decision Making
- Kurtz J.,Wortman B., 2014. ASP.NET Web API 2: Building a REST Service from Start to Finish
- Li B., Chen X.,(2014). Wavelet-based numerical analysis: A review and classification, Finite Elements in Analysis and Design, Vol. 81, pp. 14-31.
- Mallat S., (1989). A Theory for Multiresolution Signal Decomposition: The Wavelet Representation., IEEE Pattern Analysis and Machine Intelligence, vol. 11, no:7, pp. 674-693. (Ulusal - Uluslararası Makale).
- Mannheimer Paul D., (2007). The Light–Tissue Interaction of Pulse Oximetry. Anesthesia & Analgesia Vol. 105, No. 6, (Ulusal - Uluslararası Makale).
- Maillard N, Perrotton F, Delage E, Gourraud JB, Lande G, Solnon A, Probst V, Grimandi G, Clouet J. (2014). Cardiac remote monitoring in France. Archives of Cardiovascular Diseases 2014 Apr;107(4):253-60
- Oya Ş. (2011) , Bulut Bilişim, Akademik Bilişim 2011
- Hakan Y.(2012), Bulut Bilişim El Kitabı
- Prathyusha B. Rao T. S., Asha D., (2012). Extraction of Res piratory Rate from PPG Signals Using PCA and EMD, International Journal of Research in Engineering and Technology.
- Sarkar S., Bhoi A. K., ve Savita G. ,(2012). Fingertip Pulse Wave Analysis and Heart Rate Detection. International Journal of Emerging Technology and Advanced Engineering. Vol:2.
- Smith Steven W., (1999). The Scientist and Engineer's Guide to Digital Signal Processing. Second Edition (Kitap İçinde Bölüm).
- Sørensen J.T., Clemmensen P., Sejersten M. (2012) Telecardiology: past, present and future. Revista Esponela de Cardiologia
- Taşdemir C., (2014). Arduino Uygulamaları Kitabı. (Kitap İçinde Bölüm)
- Vishay, (2012). http://www.vishay.com/docs/83752/tcrt1000.pdf, (Datasheet).
- Wasilewski F. (2006). PyWavelet, Analysis and Classification of Medical Signals using Wavelet Transforms. http://www.pybytes.com/pywavelets/.
- Weeks M., (2007). Digital Signal Processing Using Matlab and Wavelets.(Kitap İçinde Bölüm).
- Zhang X., Younan N.H., (2004). A Wavelet-Based Automated Object Recognition System for Remotely Sensed Images, Proceedings of the International Conference on Imaging Science, Systems and Technology ,pp. 391-398.
Abstract
Cardiac emergencies have the critical role in the
fatal cases in our country and all over the world. Efficient and on time
emergency aid is very important for cardiac emergencies. Heart diseases and
emergency cases must be noticed as soon as possible and efforts must be taken
quickly. Patients should be taken to the nearest health center. In this study,
a new information system which includes relations of patients, doctors and
health care centers is developed for remote monitoring of patient's health status.
When emergency cases occur, this system automatically informs related
individuals and places. To analyze cardiac patient's health states some devices
such ECG, Pulse Monitor and Blood Pressure Monitor are used. We developed and
used Pulse Monitor device. We also used cloud computing to gather and analyze
patient's state records in the flexible, scalable and performance way. Cloud
computing is very advantageous to manage and centralize all important patient
data. That centralized patient data can be easily and securely used in all
platform such as mobile phones, web sites. Cloud application continuously
analyze patient data and gives feedback to the doctor's monitor in the
emergency cases.
References
- Akansu A.N., Serdjin W.A., and Selesnick, (2010). Wavelet Transforms in Signal Processing: A Review of Emerging Applications, Physical Communication, Elsevier, vol:3, issue 1, pp. 1-18. (Ulusal - Uluslararası Makale)
- Ambekar M.R., Prabhu S., (2015). A Novel Algorithm to Obtain Respiratory Rate from the PPG Signal. International Journal of Computer Applications. Vol: 126.
- Bruylants T., Munteanu A, Schelkens P.,(2015). Wavelet based volumetric medical image compression, Signal Processing: Image Communication, Vol. 31, pp. 112-133.
- Çetinkaya A., (2014). http://www.minepla.net/2014/08/wcf-ile- asp-net-web-api-nedir (Web Adresleri)
- Gavrylyuk K., (2016). https://azure.microsoft.com/en-us/documentation/articles/ app-service-mobile-value-prop (Web Adresleri)
- Grover L, (1996). A Fast Quantum Mechanical Algorithm for Database Search. Proceedings of the 28th Annual ACM Symposium on the Theory of Computing, pp.212-219.
- Gül F.T., Akif K.(2012) Giyilebilir EKG Uygulaması ve Kullanılabilir Kablosuz İletişim Teknolojilerinin Karşılaştırılması, Akademik Bilişim 2012
- I. Daubechies, (1988). Orthonormal bases of compactly supported wavelets, Comm. Pure Appl. Math. 909996.
- Jui-chien Hsieh, Meng-Wei Hsu (2012) A cloud computing based 12-lead ECG telemedicine service. BMC Medical Informatics and Decision Making
- Kurtz J.,Wortman B., 2014. ASP.NET Web API 2: Building a REST Service from Start to Finish
- Li B., Chen X.,(2014). Wavelet-based numerical analysis: A review and classification, Finite Elements in Analysis and Design, Vol. 81, pp. 14-31.
- Mallat S., (1989). A Theory for Multiresolution Signal Decomposition: The Wavelet Representation., IEEE Pattern Analysis and Machine Intelligence, vol. 11, no:7, pp. 674-693. (Ulusal - Uluslararası Makale).
- Mannheimer Paul D., (2007). The Light–Tissue Interaction of Pulse Oximetry. Anesthesia & Analgesia Vol. 105, No. 6, (Ulusal - Uluslararası Makale).
- Maillard N, Perrotton F, Delage E, Gourraud JB, Lande G, Solnon A, Probst V, Grimandi G, Clouet J. (2014). Cardiac remote monitoring in France. Archives of Cardiovascular Diseases 2014 Apr;107(4):253-60
- Oya Ş. (2011) , Bulut Bilişim, Akademik Bilişim 2011
- Hakan Y.(2012), Bulut Bilişim El Kitabı
- Prathyusha B. Rao T. S., Asha D., (2012). Extraction of Res piratory Rate from PPG Signals Using PCA and EMD, International Journal of Research in Engineering and Technology.
- Sarkar S., Bhoi A. K., ve Savita G. ,(2012). Fingertip Pulse Wave Analysis and Heart Rate Detection. International Journal of Emerging Technology and Advanced Engineering. Vol:2.
- Smith Steven W., (1999). The Scientist and Engineer's Guide to Digital Signal Processing. Second Edition (Kitap İçinde Bölüm).
- Sørensen J.T., Clemmensen P., Sejersten M. (2012) Telecardiology: past, present and future. Revista Esponela de Cardiologia
- Taşdemir C., (2014). Arduino Uygulamaları Kitabı. (Kitap İçinde Bölüm)
- Vishay, (2012). http://www.vishay.com/docs/83752/tcrt1000.pdf, (Datasheet).
- Wasilewski F. (2006). PyWavelet, Analysis and Classification of Medical Signals using Wavelet Transforms. http://www.pybytes.com/pywavelets/.
- Weeks M., (2007). Digital Signal Processing Using Matlab and Wavelets.(Kitap İçinde Bölüm).
- Zhang X., Younan N.H., (2004). A Wavelet-Based Automated Object Recognition System for Remotely Sensed Images, Proceedings of the International Conference on Imaging Science, Systems and Technology ,pp. 391-398.
Details
| Subjects | Engineering |
|---|---|
| Journal Section | Araştırma Makalesi |
| Authors | |
| Publication Date | December 15, 2016 |
| Published in Issue | Year 2016 Volume: 2 Issue: 2 |
