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Emerging wearable interfaces and algorithms for hand gesture recognition: A survey
Hands are vital in a wide range of fundamental daily activities, and neurological diseases
that impede hand function can significantly affect quality of life. Wearable hand gesture …
that impede hand function can significantly affect quality of life. Wearable hand gesture …
Wearable upper limb robotics for pervasive health: A review
Wearable robotics, also called exoskeletons, have been engineered for human-centered
assistance for decades. They provide assistive technologies for maintaining and improving …
assistance for decades. They provide assistive technologies for maintaining and improving …
Hand gesture classification framework leveraging the entropy features from sEMG signals and VMD augmented multi-class SVM
T Prabhavathy, VK Elumalai, E Balaji - Expert Systems with Applications, 2024 - Elsevier
To improve the classification accuracy of hand movements from sEMG signals, this paper
puts forward a unified hand gesture classification framework which exploits the potentials of …
puts forward a unified hand gesture classification framework which exploits the potentials of …
Effective features extraction and selection for hand gesture recognition using sEMG signal
Surface Electromyographic (sEMG) signals are a promising approach to hand and finger
gesture recognition. Most of the sEMG-based hand gesture recognition has developed …
gesture recognition. Most of the sEMG-based hand gesture recognition has developed …
Leveraging deep feature learning for wearable sensors based handwritten character recognition
Despite rapid advancements in technology, handwritten characters still hold significant roles
in various fields, including education, communication, biometric signature verification, and …
in various fields, including education, communication, biometric signature verification, and …
A reliable and efficient machine learning pipeline for american sign language gesture recognition using EMG sensors
Sign languages has extensive applications among differently-abled to communicate with
their surroundings. With the development of different sensing technologies, several new …
their surroundings. With the development of different sensing technologies, several new …
A layered sEMG–FMG hybrid sensor for hand motion recognition from forearm muscle activities
P Chen, Z Li, S Togo, H Yokoi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The activities of muscles in the forearm have been widely investigated to develop human
interfaces involving hand motions, especially in the fields of prosthetic hands and …
interfaces involving hand motions, especially in the fields of prosthetic hands and …
[HTML][HTML] Recognition of EEG signals from imagined vowels using deep learning methods
LC Sarmiento, S Villamizar, O López, AC Collazos… - Sensors, 2021 - mdpi.com
The use of imagined speech with electroencephalographic (EEG) signals is a promising
field of brain-computer interfaces (BCI) that seeks communication between areas of the …
field of brain-computer interfaces (BCI) that seeks communication between areas of the …
An efficient multi-modal sensors feature fusion approach for handwritten characters recognition using Shapley values and deep autoencoder
Handwriting is essential for the development of fine motor skills in children. Handwritten
character recognition has the potential to facilitate natural human–machine interactions …
character recognition has the potential to facilitate natural human–machine interactions …
Human reliability modeling in occupational environments toward a safe and productive operator 4.0
Many occupational environments require labor intensive activities, which could result in
fatigue and injuries and cause decreased work performance. Recently, the breakthroughs of …
fatigue and injuries and cause decreased work performance. Recently, the breakthroughs of …