Gesture Recognition Based on Deep Learning: A Review
M Wu - EAI Endorsed Transactions on e-Learning, 2024 - publications.eai.eu
Gesture recognition is an important and inevitable technology in modern times, its
appearance and improvement greatly improve the convenience of people's lives, but also …
appearance and improvement greatly improve the convenience of people's lives, but also …
[HTML][HTML] EMG-based dynamic hand gesture recognition using edge AI for human–robot interaction
ES Kim, JW Shin, YS Kwon, BY Park - Electronics, 2023 - mdpi.com
Recently, human–robot interaction technology has been considered as a key solution for
smart factories. Surface electromyography signals obtained from hand gestures are often …
smart factories. Surface electromyography signals obtained from hand gestures are often …
[HTML][HTML] A Proposal of Bioinspired Soft Active Hand Prosthesis
Soft robotics have broken the rigid wall of interaction between humans and robots due to
their own definition and manufacturing principles, allowing robotic systems to adapt to …
their own definition and manufacturing principles, allowing robotic systems to adapt to …
[HTML][HTML] Electromyogram (EMG) signal classification based on light-weight neural network with FPGAs for wearable application
HS Choi - Electronics, 2023 - mdpi.com
Recently, the application of bio-signals in the fields of health management, human–
computer interaction (HCI), and user authentication has increased. This is because of the …
computer interaction (HCI), and user authentication has increased. This is because of the …
DeepTPA-Net: A Deep Triple Attention Network for sEMG-Based Hand Gesture Recognition
The use of hand gestures for human-computer interaction (HCI) has gained popularity due
to its ability to provide natural and intuitive communication in human dialogues. Hand …
to its ability to provide natural and intuitive communication in human dialogues. Hand …
[HTML][HTML] CNN-LSTM and post-processing for EMG-based hand gesture recognition
Abstract Hand Gesture Recognition (HGR) using electromyography (EMG) signals is a
challenging problem due to the variability and noise in the signals across individuals. This …
challenging problem due to the variability and noise in the signals across individuals. This …
Wearable technologies for monitoring upper extremity functions during daily life in neurologically impaired individuals
T Proietti, A Bandini - IEEE transactions on neural systems and …, 2024 - ieeexplore.ieee.org
Neurological disorders, including stroke, spinal cord injuries, multiple sclerosis, and
Parkinson's disease, generally lead to diminished upper extremity (UE) function, impacting …
Parkinson's disease, generally lead to diminished upper extremity (UE) function, impacting …
[HTML][HTML] A 3D Printed, Bionic Hand Powered by EMG Signals and Controlled by an Online Neural Network
K Avilés-Mendoza, NG Gaibor-León, V Asanza… - Biomimetics, 2023 - mdpi.com
About 8% of the Ecuadorian population suffers some type of amputation of upper or lower
limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker …
limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker …
[HTML][HTML] Data glove-based gesture recognition using CNN-BiLSTM model with attention mechanism
J Wu, P Ren, B Song, R Zhang, C Zhao, X Zhang - Plos one, 2023 - journals.plos.org
As a novel form of human machine interaction (HMI), hand gesture recognition (HGR) has
garnered extensive attention and research. The majority of HGR studies are based on visual …
garnered extensive attention and research. The majority of HGR studies are based on visual …
Optimized k-nearest neighbors for classification of prosthetic hand movements using electromyography signal
Electromyography (EMG) signals are essential, as they are used to measure muscular
activity in different parts of the human body. The measurement and analysis of EMG signal …
activity in different parts of the human body. The measurement and analysis of EMG signal …