Biomedical signal processing
<p>Electrocardiogram (ECG) interpretation is critical for diagnosing a wide range of cardiovascular conditions. To streamline and accelerate the development of deep learning models in this domain, we present a novel, image-based version of the PTB Diagnostic ECG Database tailored for use with convolutional neural networks (CNNs), vision transformers (ViTs), and other image classification architectures. This enhanced dataset consists of 516 grayscale .png images, each representing a 12-lead ECG signal arranged as a 2D matrix (12 × T, where T is the number of time steps).
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Small intestinal serosa voltage is defined as a potential in the serosa relative to the mesentery, which provides good visualization of the neural activity and the health of the electrical activity of the Interstitial Cells of Cajal that control contractions. This dataset consists of a .csv format of porcine small intestinal serosa voltage measured during ex vivo blood reperfusion, which mimics the damage to the organ during transplantation.
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The Ground Reaction Forces are generated when walking, specifically when the foot contacts the ground, this information is directly related to the physical characteristics of each person, on the other hand, the growth that has the implementation of artificial intelligence algorithms for the diagnosis or evaluation of both pathologies and rehabilitation that occur in the lower limb are a very large area of opportunity.
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This dataset is associated with an IEEE journal submission titled: "Prediction of larynx function using multichannel surface EMG classification" by the associated authors. The dataset consists of surface electromyography (sEMG) signals recorded from 10 study participants (5 control, 5 laryngectomees), each undertaking 3 recording sessions.
During each session the following were recorded:
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