Вісник НТУУ "КПІ". Серія Радіотехніка, Радіоапаратобудування

Постійне посилання на фонд

https://ela.kpi.ua/handle/123456789/2120
ISSN 2310-0389 (Online), ISSN 2310-0397 (Print) Періодичність: 4 рази на рік
Рік заснування: 1956
Тематика: теоретична радіотехніка; електродинаміка; теорія та засоби телекомунікацій; антени та пристрої НВЧ діапазону; теорія та практика радіовимірювань; конструювання радіоапаратури; мікроелектронна та наноелектронна техніка; технологія радіоапаратобудування; засоби та методи мультимедіа; засоби захисту інформації; електронна побутова апаратура; цифрова та обчислювальна техніка; радіоелектроніка біомедичних технологій.
Офіційний сайт: https://radap.kpi.ua/radiotechnique

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Перегляд Вісник НТУУ "КПІ". Серія Радіотехніка, Радіоапаратобудування за Ключові слова "004.89"

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  • Ескіз
    ДокументВідкритий доступ
    Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques
    (КПІ ім. Ігоря Сікорського, 2024) Bondarev, V. R.; Ivanko, K. O.; Ivanushkina, N. G.
    The study is dedicated to the problem of classification of structural and functional development stage of cardiomyocytes derived from the induced pluripotent stem cells with application of the digital image processing methods and machine learning algorithms, in particular, neural networks. Cell regenerative therapy has become one of the most promising treatment options for patients with heart failure. But since cardiomyocytes are objects with a high level of complexity and have significant morphological variability, automatic classification is complicated by the lack of implemented methods. That's why researches in this area are a major global public health priority. The initial data set used in this study is a publicly open set of confocal microscopic images of cardiomyocytes which can be divided into five classes based on the morphological features (the structure of the transverse T-tubule). A small amount of input data leads to the need of using augmentation methods. Methods that prevent the alteration of the transverse T-tubule, which is an important parameter for correct classification of the development of cardiomyocytes, are used. Histogram equalization technique is used to enhance the contrast and dynamic range of the confocal microscopic images with the method of contrast-limited adaptive equalization. This helped to improve the local contrast of the analyzed images and highlight the main elements of the cardiomyocyte. Finally, Chan–Vese method, which belongs to the regional segmentation methods, is chosen for the image segmentation and removing artifacts and/or parts of other cells from the image. A pre-processed and augmented dataset is used for training of the convolutional neural network having an architecture with hierarchical structure and residual block usage. The model is evaluated based on the confusion matrix and the heat maps of different convolutional layers are analyzed. Images from the classes with a large number of mutual errors are also considered. Based on the analysis, several classes of structural and functional development of cardiomyocytes are combined. Final accuracy of the model for defining the cardiomyocytes maturation stage achieved 77%.
  • Ескіз
    ДокументВідкритий доступ
    Method for Blink Detection in Single Channel of Invasive Electromyogram Signal
    (КПІ ім. Ігоря Сікорського, 2021) Bobrov, A. L.; Borysenko, O. M.; Popov, A. O.
    Problem statement. Facial nerve damage is the cranial nervous system disorder often leading to facial muscle paralysis, which might be effectively restored using functional electrical stimulation of the fully or partially denervated circular muscle of the eye to achieve muscle contraction to close the eyelids. To control the invasive stimulation system, the automated detection of the blink event in the intact eye is used as a trigger. To achieve this, the new approach to single channel invasive electromyogram (EMG) signal analysis is proposed. Materials and Methods. The combined time-spectral approach to blink detection consists of the two stages, starting from the thresholding of filtered EMG signals in the sliding window, which is followed by comparing the total spectral power in the Fourier domain to minimum and maximum thresholds. If both conditions are met, the EMG in the current window is considered to contain the blink event. In the experiment, the EMG data recorded from the one male adult healthy volunteer is used, the signal contained an acceptable amount of artefacts and was recognized as reflecting the usual EMG. The true positive rate (TPR), positive predictive value (PPV), False Discovery Rate (FDR), and False Negative Rate (FNR) is used as a performance metrics. Results. In the result of applying the proposed blink detection algorithm with 500 ms duration of the time window and 100 ms overlap, the following performance metrics are obtained: TPR=93%, PPV=63%, FDR=7%, FNR=37%. Impact. Acceptable true positive rate of blink detection suggests the method is promising for wider applications in the clinical settings and might be incorporated in the prototypes of implanted systems for facial muscle paralysis restoration using functional electrical stimulation for further development.