Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
2 results
Search Results
Article Citation - WoS: 9Citation - Scopus: 12A Wearable Device Integrated With Deep Learning-Based Algorithms for the Analysis of Breath Patterns(Wiley, 2023) Tarım, Ergün Alperay; Tekin, Hüseyin Cumhur; Erimez, Büşra; Değirmenci, Mehmet; Tekin, H. Cumhur; 03.01. Department of Bioengineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologySleep problems are serious issues that make life difficult for all people, including sleep apnea. Sleep apnea, which causes breathlessness for more than 10 s, is linked to severe health problems due to the serious damage it can induce. To mitigate the risk of these disorders, the monitoring of patients has become increasingly challenging. Wearable technologies offer an effective healthcare solution for remote patient monitoring and diagnosis. A novel wearable system based on Arduino technology is introduced, specifically designed to monitor the breath patterns of patients. The analysis of breath data from patients holds great importance for the diagnosis and continuous monitoring of sleep apnea. To address this need, an advanced image processing system based on deep learning techniques is presented. This system automatically detects respiratory patterns, including inhalation, exhalation, and breathlessness. The device has an average of 97.6% sensitivity, 79.7% specificity, and 96% accuracy in identifying breath patterns. The designed device can offer patients and healthcare institutions a simple, inexpensive, noninvasive, and ergonomic system for the analysis of breath patterns that can be further extended for sleep apnea diagnosis.Conference Object Lots and Loop-Mediated Isothermal Amplification-Based Biosensing Using Cloud-Enabled Features(IEEE, 2022) Bayındır, Taha; Değirmenci, Mehmet; Ergenç, Ali Fuat; Elitaş, Meltem; 01. Izmir Institute of TechnologyInternet-of-Things technology (IoTs) have accelerated biosensor applications in all fields. Loop-mediated isothermal amplification (LAMP)-based biosensor technologies in conjunction with smartphone detection have been adequate to cover the demands of mobile diagnostics. The ease of use, affordability, portability, high sensitivity, flexibility, and specificity demands of point-of-care detection can be achieved by low-cost electronic components, 3-dimensional printing technologies, capturing images of calorimetrically detected readouts made our system a promising approach for real-time point-of-detection in the field. In this study, we implemented a cloud service to our LAMP-based biosensor. We previously performed bacteria detection using colony-based LAMP device and now distributed the optical readouts of the assay using smartphones. We transferred the obtained image and results of the assays through cloud. Our user-friendly interface simplifies the data processing, it directly digitized the readouts and eliminates the need of data interpretation.