Combined Neural Network Model for Detection of Electrocardiographic Changes in Partial Epileptic Patients
نویسندگان
چکیده
A combined neural network model based on the consideration that electrocardiogram (ECG) signals are chaotic signals was presented for detection of electrocardiographic changes in patients with partial epilepsy. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Two types of ECG beats (normal and partial epilepsy) were obtained from the MIT-BIH database. The computed Lyapunov exponents of the ECG signals were used as inputs of the combined neural network model and then performance of the proposed model was
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