An intelligent fault diagnosis approach for multirotor UAVs based on deep neural network of multi-resolution transform features

LA Al-Haddad, AA Jaber - Drones, 2023 - mdpi.com
As a modern technological trend, unmanned aerial vehicles (UAVs) are extensively
employed in various applications. The core purpose of condition monitoring systems …

sEMG signal processing methods: A review

J Wu, X Li, W Liu, ZJ Wang - Journal of Physics: Conference …, 2019 - iopscience.iop.org
Surface electromyography (sEMG) is one type of bioelectrical signal produced by the human
body. sEMG contains meaningful information associated with muscle activity and has …

EMG feature evaluation for improving myoelectric pattern recognition robustness

A Phinyomark, F Quaine, S Charbonnier… - Expert Systems with …, 2013 - Elsevier
In pattern recognition-based myoelectric control, high accuracy for multiple discriminated
motions is presented in most of related literature. However, there is a gap between the …

LMD based features for the automatic seizure detection of EEG signals using SVM

T Zhang, W Chen - IEEE Transactions on Neural Systems and …, 2016 - ieeexplore.ieee.org
Achieving the goal of detecting seizure activity automatically using electroencephalogram
(EEG) signals is of great importance and significance for the treatment of epileptic seizures …

A new hybrid intelligent system for accurate detection of Parkinson's disease

M Hariharan, K Polat, R Sindhu - Computer methods and programs in …, 2014 - Elsevier
Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most
common neurodegenerative disorders due to the loss of dopamine-producing brain cells …

Enhanced fault detection of wind turbine using extreme gradient boosting technique based on nonstationary vibration analysis

AAF Ogaili, MN Hamzah, AA Jaber - Journal of Failure Analysis and …, 2024 - Springer
Wind turbines serve a vital role in renewable energy generation but operate in harsh
environments and endure variable loading. Monitoring wind turbine blade conditions is …

Comparative analysis of SVM and Naive Bayes classifier for the SEMG signal classification

Y Narayan - Materials Today: Proceedings, 2021 - Elsevier
The surface electromyography (sEMG) signals are the human muscle signals which are
employed in various biomedical and engineering applications. Classification of sEMG …

Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification

M Hariharan, R Sindhu, V Vijean, H Yazid… - Computer Methods and …, 2018 - Elsevier
Background and objective Infant cry signal carries several levels of information about the
reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status …

Investigating the effect of flickering frequency pair and mother wavelet selection in steady-state visually-evoked potentials on two-command brain-computer interfaces

E Sayilgan, YK Yuce, Y Isler - Irbm, 2022 - Elsevier
Introduction Steady-state visually evoked potentials (SSVEPs) have become popular in
brain-computer interface (BCI) applications in addition to many other applications on clinical …

Feature selection based on binary tree growth algorithm for the classification of myoelectric signals

J Too, AR Abdullah, N Mohd Saad, N Mohd Ali - Machines, 2018 - mdpi.com
Electromyography (EMG) has been widely used in rehabilitation and myoelectric prosthetic
applications. However, a recent increment in the number of EMG features has led to a high …