[HTML][HTML] A review of classification techniques of EMG signals during isotonic and isometric contractions

N Nazmi, MA Abdul Rahman, SI Yamamoto, SA Ahmad… - Sensors, 2016 - mdpi.com
In recent years, there has been major interest in the exposure to physical therapy during
rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and …

EMG processing based measures of fatigue assessment during manual lifting

EF Shair, SA Ahmad, MH Marhaban… - BioMed research …, 2017 - Wiley Online Library
Manual lifting is one of the common practices used in the industries to transport or move
objects to a desired place. Nowadays, even though mechanized equipment is widely …

Walking gait event detection based on electromyography signals using artificial neural network

N Nazmi, MAA Rahman, SI Yamamoto… - … Signal Processing and …, 2019 - Elsevier
In many gait applications, the focal events are the stance and swing phases. Although
detecting gait events using electromyography signals will help the development of assistive …

Multiday evaluation of techniques for EMG-based classification of hand motions

A Waris, IK Niazi, M Jamil, K Englehart… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Currently, most of the adopted myoelectric schemes for upper limb prostheses do not
provide users with intuitive control. Higher accuracies have been reported using different …

Automated stratification of liver disease in ultrasound: an online accurate feature classification paradigm

L Saba, N Dey, AS Ashour, S Samanta, SS Nath… - Computer methods and …, 2016 - Elsevier
Purpose Fatty liver disease (FLD) is one of the most common diseases in liver. Early
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …

[HTML][HTML] A deep learning approach to EMG-based classification of gait phases during level ground walking

C Morbidoni, A Cucchiarelli, S Fioretti, F Di Nardo - Electronics, 2019 - mdpi.com
Correctly identifying gait phases is a prerequisite to achieve a spatial/temporal
characterization of muscular recruitment during walking. Recent approaches have …

Hand medical monitoring system based on machine learning and optimal EMG feature set

M Yu, G Li, D Jiang, G Jiang, B Tao, D Chen - Personal and Ubiquitous …, 2023 - Springer
Considering that serious hand function damage will greatly affect the daily life of patients, its
recovery mainly depends on the regular inspection and manual training of medical staff, and …

Nonnegative matrix factorization for the identification of EMG finger movements: Evaluation using matrix analysis

GR Naik, HT Nguyen - IEEE journal of biomedical and health …, 2014 - ieeexplore.ieee.org
Surface electromyography (sEMG) is widely used in evaluating the functional status of the
hand to assist in hand gesture recognition, prosthetics and rehabilitation applications. The …

Application of PSO-RBF neural network in gesture recognition of continuous surface EMG signals

M Yu, G Li, D Jiang, G Jiang, F Zeng… - Journal of Intelligent …, 2020 - content.iospress.com
In view of the fact that independent gesture recognition cannot fully meet the natural,
convenient and effective needs of actual human-computer interaction, this paper analyzes …

Classification of ECG signal during atrial fibrillation using autoregressive modeling

K Padmavathi, KS Ramakrishna - Procedia Computer Science, 2015 - Elsevier
Atrial fibrillation (AF) is a common type of arrhythmia that causes death in the adults. The
Auto regressive (AR) coefficients characterize the features of AF. The AR coefficients are …