With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …

Epilepsy is the neurological disorder of the brain which is difficult to diagnose visually using
Electroencephalogram (EEG) signals. Hence, an automated detection of epilepsy using …

Entropy is a powerful tool for the analysis of time series, as it allows describing the
probability distributions of the possible state of a system, and therefore the information …

Permutation entropy (PE) has been recently suggested as a novel measure to characterize
the complexity of nonlinear time series. In this paper, we propose a simple method to …

The electroencephalogram (EEG) has proven a valuable tool in the study and detection of
epilepsy. This paper investigates for the first time the use of Permutation Entropy (PE) as a …

A new bearing vibration feature extraction method based on multiscale permutation entropy
(MPE) and improved support vector machine based binary tree (ISVM-BT) is put forward in …

Sleep scoring is one of the most important diagnostic methods in psychiatry and neurology.
Sleep staging is a time consuming and difficult task undertaken by sleep experts. This study …

More than ten years ago Bandt and Pompe introduced a new measure to quantify
complexity in measured time series. During these ten years, this measure has been modified …

This paper investigates the usage of permutation entropy for working status characterization
of rotary machines. As a statistical measure, the permutation entropy describes complexity of …

Bearing fault diagnosis has attracted significant attention over the past few decades. It
consists of two major parts: vibration signal feature extraction and condition classification for …