Abstract
The article proposes a study of cardiac arrhythmia detection, because besides the elderly this type of anomaly can occur with adolescents as well. During an arrhythmia the heart may beat very fast, very slow, or with an irregular rhythm. Often the physician may have difficulty detecting which type of arrhythmia, so a system will be proposed to assist in the medical diagnosis to detect arrhythmia in the patient. For this will be a database of ECG signal of several patients, where was applied an ANN (Artificial Neural Network with ELM training) to make the classification. Both standardized and raw data were used during the training stage, as well as several neuron architectures in the hidden layer were tested to have a good accuracy that will be the metric used in the work.
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Lima, J.C.C., de Lima, A.F., Souza, D.A., Tonieto, M.T., Batista, J.G., de Oliveira, M.E.N. (2020). Cardiac Arrhythmia Detection Using Computational Intelligence Techniques Based on ECG Signals. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_48
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DOI: https://doi.org/10.1007/978-3-030-45691-7_48
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