Açık Akademik Arşiv Sistemi

A New Approach For Treatment of Chronic Obstructive Pulmonary Disease

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dc.contributor.authors Orenc, S; Ucar, MK; Bozkurt, MR; Bilgin, C;
dc.date.accessioned 2020-02-27T08:26:53Z
dc.date.available 2020-02-27T08:26:53Z
dc.date.issued 2017
dc.identifier.citation Orenc, S; Ucar, MK; Bozkurt, MR; Bilgin, C; (2017). A New Approach For Treatment of Chronic Obstructive Pulmonary Disease. 2017 MEDICAL TECHNOLOGIES NATIONAL CONGRESS (TIPTEKNO), , -
dc.identifier.uri https://hdl.handle.net/20.500.12619/65890
dc.description.abstract Chronic Obstructive Pulmonary Disease (COPD) is a persistent respiratory disease usually caused by toxic gases. The diagnosis is made by a specialist doctor on a report taken by a specialist technician using a spirometer. Diagnostic steps can only be carried out in hospital environment in the presence of a qualified technician. The diagnostic process is so troublesome that it leads to alternative system requirements. In this study, a portable software system based on photoplethysmography signal is proposed as an alternative method to reduce the burden of the diagnosis process of the disease. For this purpose, 26 features were extracted from the photoplethysmography signal in time domain. The extracted features were classified by machine learning based k - Nearest Neighbors algorithm and tried to diagnose the disease. The study included 8 patients with COPD and a control group of 6 patients. Parameters such as accuracy, sensitivity, specificity and f-metric were used to calculate the classification performance. According to some k values and distance algorithms, all data are correctly classified as % 100, with a sensitivity of 1, a specificity of 1 and a measurement of F of 1. Given the results of the study, it has come to the conclusion that machine learning-based COPD diagnosis can be done effectively and productively.
dc.language Turkish
dc.publisher IEEE
dc.subject Engineering
dc.title A New Approach For Treatment of Chronic Obstructive Pulmonary Disease
dc.type Proceedings Paper
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Elektrik-Elektronik Mühendisliği Bölümü
dc.contributor.saüauthor Uçar, Muhammed Kürşad
dc.contributor.saüauthor Bozkurt, Mehmet Recep
dc.contributor.saüauthor Bilgin, Cahit
dc.identifier.wos WOS:000427649500008
dc.contributor.author Sedat Orenc
dc.contributor.author Uçar, Muhammed Kürşad
dc.contributor.author Bozkurt, Mehmet Recep
dc.contributor.author Bilgin, Cahit

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