4 papers with code • 3 benchmarks • 0 datasets
Our approach based on an ensemble of SVMs offered a satisfactory performance, improving the results when compared to a single SVM model using the same features.
Electrocardiogram (ECG) signal is a common and powerful tool to study heart function and diagnose several abnormal arrhythmia.
Ranked #1 on Arrhythmia Detection on MIT-BIH AR
Electrocardiogram (ECG) can be reliably used as a measure to monitor the functionality of the cardiovascular system.
It makes fundamental improvements over the mainstream temporal convolutional neural networks, including the incorporation of separable depth-wise convolution to reduce the computational complexity of the model and residual connections as time attention machines, increase the network depth and accuracy.