A review in gait rehabilitation devices and applied control techniques
SL Chaparro-Cárdenas… - Disability and …, 2018 - Taylor & Francis
Purpose: The aim of this review is to analyse the different existing technologies for gait
rehabilitation, focusing mainly in robotic devices. Those robots help the patient to recover a …
rehabilitation, focusing mainly in robotic devices. Those robots help the patient to recover a …
[PDF][PDF] Classification of hand movements based on discrete wavelet transform and enhanced feature extraction
Extraction of potential electromyography (EMG) features has become one of the important
roles in EMG pattern recognition. In this paper, two EMG features, namely, enhanced …
roles in EMG pattern recognition. In this paper, two EMG features, namely, enhanced …
Maintenance management of wind turbines structures via mfcs and wavelet transforms
RR de la Hermosa González, FPG Márquez… - … and Sustainable Energy …, 2015 - Elsevier
This paper introduces a novel Fault Detection and Diagnosis method based on the wavelet
transform to detect defects on the tower of a wind turbine. 24 Macro-Fiber Composite …
transform to detect defects on the tower of a wind turbine. 24 Macro-Fiber Composite …
Application of wavelet analysis in EMG feature extraction for pattern classification
A Phinyomark, C Limsakul… - Measurement Science …, 2011 - sciendo.com
Nowadays, analysis of electromyography (EMG) signal using wavelet transform is one of the
most powerful signal processing tools. It is widely used in the EMG recognition system. In …
most powerful signal processing tools. It is widely used in the EMG recognition system. In …
Feature extraction and reduction of wavelet transform coefficients for EMG pattern classification
A Phinyomark, A Nuidod, P Phukpattaranont… - Elektronika ir …, 2012 - eejournal.ktu.lt
Recently, wavelet analysis has proved to be one of the most powerful signal processing
tools for the analysis of surface electromyography (sEMG) signals. It has been widely used …
tools for the analysis of surface electromyography (sEMG) signals. It has been widely used …
Skin-integrated, biocompatible, and stretchable silicon microneedle electrode for long-term EMG monitoring in motion scenario
Electromyography (EMG) signal is the electrical potential generated by contracting muscle
cells. Long-term and accurate EMG monitoring is desirable for neuromuscular function …
cells. Long-term and accurate EMG monitoring is desirable for neuromuscular function …
Computational methods of EEG signals analysis for Alzheimer's disease classification
Computational analysis of electroencephalographic (EEG) signals have shown promising
results in detecting brain disorders, such as Alzheimer's disease (AD). AD is a progressive …
results in detecting brain disorders, such as Alzheimer's disease (AD). AD is a progressive …
Characterization of biomedical signals: Feature engineering and extraction
B Rajoub - Biomedical signal processing and artificial intelligence …, 2020 - Elsevier
Abstract Characterization of biomedical signals is challenging because of noise, stochastic
nature of the signals, and the large variability both within and between individuals. This …
nature of the signals, and the large variability both within and between individuals. This …
An automatic mobile-health based approach for EEG epileptic seizures detection
MEL Menshawy, A Benharref, M Serhani - Expert systems with applications, 2015 - Elsevier
In this article, we develop a comprehensive mobile-based approach, which is able to
perform the essential processes needed to automatically analyze and detect epileptic …
perform the essential processes needed to automatically analyze and detect epileptic …
[PDF][PDF] A detail study of wavelet families for EMG pattern recognition
Wavelet transform (WT) has recently drawn the attention of the researchers due to its
potential in electromyography (EMG) recognition system. However, the optimal mother …
potential in electromyography (EMG) recognition system. However, the optimal mother …