Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a
motor. Deep learning provides a powerful ability to extract the features of raw data …

In recent years, the usage of portable electroencephalogram (EEG) devices are becoming
popular for both clinical and non-clinical applications. In order to provide more comfort to the …

Human gait activity recognition is an emerging field of motion analysis that can be applied in
various application domains. One of the most attractive applications includes monitoring of …

Brain-computer interfaces (BCIs) aim to directly bridge the human brain and the outside
world through acquiring and processing the brain signals in real time. In recent two decades …

In recent years, there has been an increase in the usage of consumer based EEG devices
with fewer channel configuration. Although independent component analysis has been a …

Sleep is one of the prime natural activities for human well-being in physical, emotional, and
mental aspects. The assessment of sleep electroencephalography (EEG) signals is required …

Introduction Steady-state visually evoked potentials (SSVEPs) have become popular in
brain-computer interface (BCI) applications in addition to many other applications on clinical …

In this article, we propose a novel wavelet convolution unit for the image-oriented neural
network to integrate wavelet analysis with a vanilla convolution operator to extract deep …

Gait event detection is a crucial step towards the effective assessment and rehabilitation of
motor dysfunctions. Recently, the continuous wavelet transform (CWT) based methods have …

Wavelet transform (WT) is an important tool to analyze the time-frequency structure of a
signal. The WT relies on a prototype signal that is called the mother wavelet. However, there …