Emerging wearable interfaces and algorithms for hand gesture recognition: A survey

S Jiang, P Kang, X Song, BPL Lo… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
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 …

Wearable upper limb robotics for pervasive health: A review

C Ochieze, S Zare, Y Sun - Progress in Biomedical Engineering, 2023 - iopscience.iop.org
Wearable robotics, also called exoskeletons, have been engineered for human-centered
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 …

Effective features extraction and selection for hand gesture recognition using sEMG signal

ASM Miah, J Shin, MAM Hasan - Multimedia Tools and Applications, 2024 - Springer
Surface Electromyographic (sEMG) signals are a promising approach to hand and finger
gesture recognition. Most of the sEMG-based hand gesture recognition has developed …

Leveraging deep feature learning for wearable sensors based handwritten character recognition

SK Singh, A Chaturvedi - Biomedical Signal Processing and Control, 2023 - Elsevier
Despite rapid advancements in technology, handwritten characters still hold significant roles
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

SK Singh, A Chaturvedi - Multimedia Tools and Applications, 2023 - Springer
Sign languages has extensive applications among differently-abled to communicate with
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 …

[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 …

An efficient multi-modal sensors feature fusion approach for handwritten characters recognition using Shapley values and deep autoencoder

SK Singh, A Chaturvedi - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Handwriting is essential for the development of fine motor skills in children. Handwritten
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

SK Kheiri, Z Vahedi, H Sun, FM Megahed… - International Journal of …, 2023 - Elsevier
Many occupational environments require labor intensive activities, which could result in
fatigue and injuries and cause decreased work performance. Recently, the breakthroughs of …