Gesture recognition using surface electromyography and deep learning for prostheses hand: state-of-the-art, challenges, and future

W Li, P Shi, H Yu - Frontiers in neuroscience, 2021 - frontiersin.org
Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …

A review on electromyography decoding and pattern recognition for human-machine interaction

M Simao, N Mendes, O Gibaru, P Neto - Ieee Access, 2019 - ieeexplore.ieee.org
This paper presents a literature review on pattern recognition of electromyography (EMG)
signals and its applications. The EMG technology is introduced and the most relevant …

[HTML][HTML] Intelligent human computer interaction based on non redundant EMG signal

Y Sun, C Xu, G Li, W Xu, J Kong, D Jiang, B Tao… - Alexandria Engineering …, 2020 - Elsevier
Human computer interaction plays an increasingly important role in our life. People need
more intelligent, concise and efficient human-computer interaction. It is of great significance …

EMG-centered multisensory based technologies for pattern recognition in rehabilitation: state of the art and challenges

C Fang, B He, Y Wang, J Cao, S Gao - Biosensors, 2020 - mdpi.com
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …

On overview of PCA application strategy in processing high dimensionality forensic data

LC Lee, AA Jemain - Microchemical Journal, 2021 - Elsevier
Principal component analysis (PCA) is very useful for data exploration owing to its
unsupervised nature; and has been proven to be a powerful multivariate exploratory tool for …

Personalized variable gain control with tremor attenuation for robot teleoperation

C Yang, J Luo, Y Pan, Z Liu… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Teleoperated robot systems are able to support humans to accomplish their tasks in many
applications. However, the performance of teleoperation largely depends on motor …

Noninvasive neural interfacing with wearable muscle sensors: Combining convolutive blind source separation methods and deep learning techniques for neural …

A Holobar, D Farina - IEEE signal processing magazine, 2021 - ieeexplore.ieee.org
Neural interfacing is essential for advancing our fundamental understanding of movement
neurophysiology and for developing human-machine interaction systems. This can be …

Haptics electromyography perception and learning enhanced intelligence for teleoperated robot

C Yang, J Luo, C Liu, M Li… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Due to the lack of transparent and friendly human-robot interaction (HRI) interface, as well
as various uncertainties, it is usually a challenge to remotely manipulate a robot to …

Causes of performance degradation in non-invasive electromyographic pattern recognition in upper limb prostheses

I Kyranou, S Vijayakumar, MS Erden - Frontiers in neurorobotics, 2018 - frontiersin.org
Surface Electromyography (EMG)-based pattern recognition methods have been
investigated over the past years as a means of controlling upper limb prostheses. Despite …

Methodology of surface electromyography in gait analysis: review of the literature

GI Papagiannis, AI Triantafyllou… - Journal of medical …, 2019 - Taylor & Francis
Gait analysis is a significant diagnostic procedure for the clinicians who manage
musculoskeletal disorders. Surface electromyography (sEMG) combined with kinematic and …