Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Tarım, Ergün AlperayWoS Q: search.filters.wosQuartile.Q1

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  • Article
    Citation - WoS: 9
    Citation - Scopus: 12
    A Wearable Device Integrated With Deep Learning-Based Algorithms for the Analysis of Breath Patterns
    (Wiley, 2023) Tarım, Ergün Alperay; Erimez, Büşra; Değirmenci, Mehmet; Tekin, H. Cumhur
    Sleep 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.
  • Article
    Citation - WoS: 15
    Citation - Scopus: 16
    Electromechanical Rt-Lamp Device for Portable Sars-Cov Detection
    (Elsevier, 2023) Tarım, Ergün Alperay; Öksüz, Cemre; Karakuzu, Betül; Appak, Özgür; Sayıner, Ayça Arzu; Tekin, Hüseyin Cumhur
    Rapid point-of-care tests for infectious diseases are essential, especially in pandemic conditions. We have developed a point-of-care electromechanical device to detect SARS-CoV-2 viral RNA using the reverse-transcription loop-mediated isothermal amplification (RT-LAMP) principle. The developed device can detect SARS-CoV-2 viral RNA down to 103 copies/mL and from a low amount of sample volumes (2 μL) in less than an hour of standalone operation without the need for professional labor and equipment. Integrated Peltier elements in the device keep the sample at a constant temperature, and an integrated camera allows automated monitoring of LAMP reaction in a stirring sample by using colorimetric analysis of unfocused sample images in the hue/saturation/value color space. This palm-fitting, portable and low-cost device does not require a fully focused sample image for analysis, and the operation could be stopped automatically through image analysis when the positive test results are obtained. Hence, viral infections can be detected with the portable device produced without the need for long, expensive, and labor-intensive tests and equipment, which can make the viral tests disseminated at the point-of-care.