E2cnn: An efficient concatenated cnn for classification of surface emg extracted from upper limb

MF Qureshi, Z Mushtaq, MZU Rehman… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Surface electromyography is a bioelectrical indicator that emerges during muscle
contraction and has been widely used in a variety of clinical applications. Several prosthetic …

Spectral image-based multiday surface electromyography classification of hand motions using CNN for human–computer interaction

MF Qureshi, Z Mushtaq, MZ ur Rehman… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Physiological signals such as electromyography (EMG) have been used in human–
computer interaction (HCI) for medical applications. Wearable prostheses, such as robotic …

Supervised myoelectrical hand gesture recognition in post-acute stroke patients with upper limb paresis on affected and non-affected sides

A Anastasiev, H Kadone, A Marushima, H Watanabe… - Sensors, 2022 - mdpi.com
In clinical practice, acute post-stroke paresis of the extremities fundamentally complicates
timely rehabilitation of motor functions; however, recently, residual and distorted …

Induction of neural plasticity using a low-cost open source brain-computer interface and a 3D-printed wrist exoskeleton

M Jochumsen, TAM Janjua, JC Arceo, J Lauber… - Sensors, 2021 - mdpi.com
Brain-computer interfaces (BCIs) have been proven to be useful for stroke rehabilitation, but
there are a number of factors that impede the use of this technology in rehabilitation clinics …

[HTML][HTML] Conformal, stretchable, breathable, wireless epidermal surface electromyography sensor system for hand gesture recognition and rehabilitation of stroke …

K Yang, S Zhang, Y Yang, X Liu, J Li, B Bao, C Liu… - Materials & Design, 2024 - Elsevier
Surface electromyography (sEMG) plays a significant role in the everyday practice of clinic
hand function rehabilitation. The materials and design of current typical clinic sEMG …

[PDF][PDF] EMG Signal Acquisition and Processing for Feature Extraction And Detection of Disease

S Chatterjee, A Chatterjee, S Saha, D Mukherjee… - J. Eng. Technol …, 2024 - jet-m.com
Electromyography (EMG) is a diagnostic procedure for evaluating the health of muscles and
the nerve cells that control them. Proper analysis of the results of EMG can reveal muscle …

Facial EMG activity is associated with hedonic experiences but not nutritional values while viewing food images

W Sato, S Yoshikawa, T Fushiki - Nutrients, 2020 - mdpi.com
The physiological correlates of hedonic/emotional experiences to visual food stimuli are of
theoretical and practical interest. Previous psychophysiological studies have shown that …

Electromyography based hand movement classification and feature extraction using machine learning algorithms

E Ekinci, Z Garip, K Serbest - Politeknik Dergisi, 2023 - dergipark.org.tr
The categorization of hand gestures holds significant importance in controlling orthotic and
prosthetic devices, enabling human-machine interaction, and facilitating telerehabilitation …

Deep Learning Based Post-stroke Myoelectric Gesture Recognition: From Feature Construction to Network Design

T Bao, Z Lu, P Zhou - IEEE Transactions on Neural Systems …, 2024 - ieeexplore.ieee.org
Recently, robot-assisted rehabilitation has emerged as a promising solution to increase the
training intensity of stroke patients while reducing workload on therapists, whilst surface …

[HTML][HTML] Data-Driven Stroke Classification Utilizing Electromyographic Muscle Features and Machine Learning Techniques

J Lee, Y Kim, E Kim - Applied Sciences, 2024 - mdpi.com
Background: Predicting a stroke in advance or through early detection of subtle prodromal
symptoms is crucial for determining the prognosis of the remaining life. Electromyography …