In this study we have proposed and compared use of CWT (Continues Wavelet Transform)
with two powerful data transformation techniques DWT (Discrete Wavelet Transform), and …

In this study, new neural network models with adaptive activation function (NNAAF) were
implemented to classify ECG arrhythmias. Our NNAAF models included three types named …

We provide a comprehensive account of recent advances in biomedical image analysis and
classification from two complementary imaging modalities: terahertz (THz) pulse imaging …

[Purpose] Intelligent emotion assessment systems have been highly successful in a variety
of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to …

The ECG uses some methods to diagnose these cardiac arrhythmias and tries to correct the
diagnosis. ECG signals are characterized by a collection of waves such as P, Q, R, S, T …

ECG signals are an important source of information in the diagnosis of atrial conduction
pathology. Nevertheless, diagnosis by visual inspection is a difficult task. This work …

Premature ventricular contraction (PVC) is a common type of abnormal heartbeat. Without
early diagnosis and proper treatment, PVC may result in serious harms. Diagnosis of PVC is …

This paper presents the new automated detection method for electrocardiogram (ECG)
arrhythmias. The detection system is implemented with integration of complex valued feature …

Electrocardiograms (ECG) are extensively used for the diagnosis of cardiac arrhythmias.
This work investigates the use of machine learning classification algorithms for ECG …

Objective We provide a survey of recent advances in biomedical image analysis and
classification from emergent imaging modalities such as terahertz (THz) pulse imaging (TPI) …