A review of hand gesture and sign language recognition techniques
Hand gesture recognition serves as a key for overcoming many difficulties and providing
convenience for human life. The ability of machines to understand human activities and their …
convenience for human life. The ability of machines to understand human activities and their …
Robhand: A hand exoskeleton with real-time emg-driven embedded control. quantifying hand gesture recognition delays for bilateral rehabilitation
Assisted bilateral rehabilitation has been proven to help patients improve their paretic limb
ability and promote motor recovery, especially in upper limbs, after suffering a …
ability and promote motor recovery, especially in upper limbs, after suffering a …
Electromyogram-based classification of hand and finger gestures using artificial neural networks
Electromyogram (EMG) signals have been increasingly used for hand and finger gesture
recognition. However, most studies have focused on the wrist and whole-hand gestures and …
recognition. However, most studies have focused on the wrist and whole-hand gestures and …
Real-time surface EMG pattern recognition for hand gestures based on an artificial neural network
Z Zhang, K Yang, J Qian, L Zhang - Sensors, 2019 - mdpi.com
In recent years, surface electromyography (sEMG) signals have been increasingly used in
pattern recognition and rehabilitation. In this paper, a real-time hand gesture recognition …
pattern recognition and rehabilitation. In this paper, a real-time hand gesture recognition …
An experimental study on upper limb position invariant EMG signal classification based on deep neural network
AK Mukhopadhyay, S Samui - Biomedical signal processing and control, 2020 - Elsevier
The classification of surface electromyography (sEMG) signal has an important usage in the
man-machine interfaces for proper controlling of prosthetic devices with multiple degrees of …
man-machine interfaces for proper controlling of prosthetic devices with multiple degrees of …
Hyperdimensional biosignal processing: A case study for EMG-based hand gesture recognition
The mathematical properties of high-dimensional spaces seem remarkably suited for
describing behaviors produces by brains. Brain-inspired hyperdimensional computing …
describing behaviors produces by brains. Brain-inspired hyperdimensional computing …
A versatile embedded platform for EMG acquisition and gesture recognition
Wearable devices offer interesting features, such as low cost and user friendliness, but their
use for medical applications is an open research topic, given the limited hardware resources …
use for medical applications is an open research topic, given the limited hardware resources …
Discrimination of EMG signals using a neuromorphic implementation of a spiking neural network
An accurate description of muscular activity plays an important role in the clinical diagnosis
and rehabilitation research. The electromyography (EMG) is the most used technique to …
and rehabilitation research. The electromyography (EMG) is the most used technique to …
A novel feature extraction method for machine learning based on surface electromyography from healthy brain
G Li, J Li, Z Ju, Y Sun, J Kong - Neural Computing and Applications, 2019 - Springer
Feature extraction is one of most important steps in the control of multifunctional prosthesis
based on surface electromyography (sEMG) pattern recognition. In this paper, a new sEMG …
based on surface electromyography (sEMG) pattern recognition. In this paper, a new sEMG …
deepGesture: Deep learning-based gesture recognition scheme using motion sensors
Recent advancement in smart phones and sensor technology has promoted research in
gesture recognition. This has made designing of efficient gesture interface easy. However …
gesture recognition. This has made designing of efficient gesture interface easy. However …