Publication: Solunum Apnesi Tespiti için Solunum Hızını Ölçmeye Dayalı Akıllı Bir Sistem Tasarımı ve Uygulaması
Abstract
Bir hasta için en önemli kriter, yaşamsal parametrelerinin takibidir. Bunlar; solunum, vücut sıcaklığı, oksijen satürasyonu, kan basıncı ve nabızdır. Vital parametrelerden biri olan solunum, aslında birçok yaşamsal parametreyi de etkileyen aynı zamanda metabolik ve kardiyovasküler bozukluklar gibi patalojik durumlar hakkında da bilgiler vermesi sebebiyle fazlasıyla kritiktir. Solunum ölçümü için çoğunlukla mevcut olarak kullanılan yöntem, manuel yöntemdir. Bunun yanı sıra sürekli takip gerektiren hastalar için de kullanılan biyomedikal cihazlar mevcuttur. Fakat son zamanlarda hasta takibinin zorlaşması sebebiyle (Covid-19 hastalığı nedeniyle yoğun bakımlarda yaşanan yoğunluklar gibi) solunum takibi için yeni yollar aranmaktadır. Güvenilir, kolay, hızlı ve mümkün olduğu sürece uygun maliyetli bir sistem ile solunum takibi, hem hasta yoğunluğunun giderilmesi hem de önemli bir yaşamsal parametrenin takibi açısından önemli ve gereklidir. Bu tez çalışmasında, farklı sensörlerden eş zamanlı veriler alınarak solunum hızı ölçümü için akıllı bir sitem tasarımı yapılması amaçlanmıştır. Bu amaç doğrultusunda beş kişiden (dört kadın, bir erkek) piezo sensör, polivinildin florür (PVDF) film sensör ve termistör kullanılarak eş zamanlı alınan otuz iki farklı analog sinyal, bir mikrodenetleyici sayesinde sayısallaştırılarak bilgisayara aktarılmıştır. Vücudun çeşitli bölgelerinden(thorax, trakea, burun kenarı) alınan solunum sinyalleri, önişleme süreçlerinden geçirilerek sürekli zaman dalgacık dönüşümü tabanlı geliştirilen sistem ile analiz edilmiştir. Bu analiz sonucunda, amaçlandığı gibi kullanılan sensörlerin her biriyle ayrı ayrı solunum hızı takibinin yapılabileceği anlaşılmıştır. Bütün bu çalışmalara ek olarak solunum hızı araştırmaları yapılırken solunum sıkıntısı olan bazı hastalarda meydana gelen solunum apnesi (durması) durumunun da analiz edilebilme ihtimalinin olduğu görülmüştür. Aynı zamanda veri alınırken solunum durması tespiti için gönüllülerden, yapay apne oluşturularak veri alınmıştır. Solunum hızında yakalanan başarının, apne tespitinde sensörlere göre değiştiği görülmüştür. Solunum apnesi, en doğru şekilde piezo sensörler tarafından tespit edilmiştir.
The most important criterion for a patient is the monitoring of vital parameters. These; respiration, body temperature, oxygen saturation, blood pressure and pulse. Respiration, which is one of the vital parameters, is extremely critical because it affects many vital parameters and also provides information about pathological conditions such as metabolic and cardiovascular disorders. The mostly currently used method for respiratory measurement is the manual method. In addition, there are biomedical devices used for patients who require continuous follow-up. However, recently, due to the difficulty of patient follow-up (such as the intensity experienced in intensive care units due to Covid-19 disease), new ways are sought for respiratory follow-up. Respiratory monitoring with a reliable, easy, fast and cost-effective system as long as possible is important and necessary in terms of both eliminating patient density and monitoring an important vital parameter. In this thesis, it is aimed to design an intelligent system for respiratory rate measurement by taking simultaneous data from different sensors. For this purpose, thirty-two different analog signals taken simultaneously from five people (four women, one man) using a piezo sensor, polyvinyldine fluoride (PVDF) film sensor and thermistor were digitized and transferred to the computer by means of a microcontroller. Respiratory signals received from various parts of the body (thorax, trachea, nose edge) were analyzed with a system developed based on continuous time wavelet transform by passing through preprocessing processes. As a result of this analysis, it was understood that respiratory rate can be followed separately with each of the sensors used as intended. In addition to all these studies, it was observed that respiratory apnea (cessation) that occurred in some patients with respiratory distress could also be analyzed while researching respiratory rate. At the same time, data were obtained from the volunteers by creating artificial apnea to detect respiratory arrest while taking data. It has been observed that the success achieved in respiratory rate varies according to the sensors in apnea detection. Apnea was most accurately detected by piezo sensors.
The most important criterion for a patient is the monitoring of vital parameters. These; respiration, body temperature, oxygen saturation, blood pressure and pulse. Respiration, which is one of the vital parameters, is extremely critical because it affects many vital parameters and also provides information about pathological conditions such as metabolic and cardiovascular disorders. The mostly currently used method for respiratory measurement is the manual method. In addition, there are biomedical devices used for patients who require continuous follow-up. However, recently, due to the difficulty of patient follow-up (such as the intensity experienced in intensive care units due to Covid-19 disease), new ways are sought for respiratory follow-up. Respiratory monitoring with a reliable, easy, fast and cost-effective system as long as possible is important and necessary in terms of both eliminating patient density and monitoring an important vital parameter. In this thesis, it is aimed to design an intelligent system for respiratory rate measurement by taking simultaneous data from different sensors. For this purpose, thirty-two different analog signals taken simultaneously from five people (four women, one man) using a piezo sensor, polyvinyldine fluoride (PVDF) film sensor and thermistor were digitized and transferred to the computer by means of a microcontroller. Respiratory signals received from various parts of the body (thorax, trachea, nose edge) were analyzed with a system developed based on continuous time wavelet transform by passing through preprocessing processes. As a result of this analysis, it was understood that respiratory rate can be followed separately with each of the sensors used as intended. In addition to all these studies, it was observed that respiratory apnea (cessation) that occurred in some patients with respiratory distress could also be analyzed while researching respiratory rate. At the same time, data were obtained from the volunteers by creating artificial apnea to detect respiratory arrest while taking data. It has been observed that the success achieved in respiratory rate varies according to the sensors in apnea detection. Apnea was most accurately detected by piezo sensors.
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