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Implementation of a study which attempt to evaluate whether the stability of decomposed ECG subsystems can be analyzed in order to effectively investigate the overall performance of ECG signals, and aid in disease diagnosis
This code for how to calculate the heart rate of someone using his ECG data on Matlab and ploting His ECG in addition determining if his HR is normal or Abnormal
ARCHIVED - Kronecker technique for improving quality of the signal in compressive sensing recovery. Transposing to Python, to the best of my ability, the work from https://github.com/hadizand/Kronecker-based-CS-recovery. (Originally in MATLAB)
Implement an intelligent diagnostic system capable of accurately classifying cardiac activity. By analyzing ECG images or electronic readings, the system aims to detect various abnormalities, including distinguishing normal vs. abnormal heartbeats, identifying myocardial infarction (MI) and its history, and assessing the impact of COVID-19.
The project involves developing a Python library for ECG compressed sensing. The software will include modules for data reading, visualization, compressed-sensing, reconstruction, and evaluation.
Left Ventricular Hypertrophy (LVI) diagnosis using Machine Learning methods (K-means and KNN) and feature extraction techniques of electrocardiogram (ECG) signals.