Publications by authors named "Sedong Min"

Center of pressure refers to the centroid of the ground reaction force vector detected underneath the walking foot, which is a summary measure representing body segment movements during human locomotion. In this study, we developed a cost-effective, lightweight insole-type textile capacitive sensor (I-TCPs) to analyze plantar pressure (PP) distribution and center of pressure (COP) trajectory. To test the accuracy of I-TCPs, the measured pressure data was compared with that of F-scan.

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Article Synopsis
  • The paper discusses a deep learning method that utilizes transfer learning to classify lung diseases from chest X-ray images, aiming to enhance the accuracy and efficiency of computer-aided diagnostic systems.
  • The proposed method employs an end-to-end learning approach using the EfficientNet v2-M model to directly analyze raw chest X-ray images for identifying diseases.
  • Experiments on two different data sets (NIH and Cheonan Soonchunhyang University Hospital) demonstrated promising results, with accuracy rates around 82% and high specificity, especially for tuberculosis detection, showcasing the method's effectiveness in lung disease diagnosis.
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The lower limb joints might be affected by different shoe types and gait speeds. Monitoring joint angles might require skill and proper technique to obtain accurate data for analysis. We aimed to estimate the knee joint angle using a textile capacitive sensor and artificial neural network (ANN) implementing with three shoe types at two gait speeds.

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Deep Learning (DL), a successful promising approach for discriminative and generative tasks, has recently proved its high potential in 2D medical imaging analysis; however, physiological data in the form of 1D signals have yet to be beneficially exploited from this novel approach to fulfil the desired medical tasks. Therefore, in this paper we survey the latest scientific research on deep learning in physiological signal data such as electromyogram (EMG), electrocardiogram (ECG), electroencephalogram (EEG), and electrooculogram (EOG). We found 147 papers published between January 2018 and October 2019 inclusive from various journals and publishers.

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