EMG pattern recognition in the era of big data and deep learning
A Phinyomark, E Scheme - Big Data and Cognitive Computing, 2018 - mdpi.com
The increasing amount of data in electromyographic (EMG) signal research has greatly
increased the importance of developing advanced data analysis and machine learning …
increased the importance of developing advanced data analysis and machine learning …
A review of hand gesture recognition systems based on noninvasive wearable sensors
R Tchantchane, H Zhou, S Zhang… - Advanced Intelligent …, 2023 - Wiley Online Library
Hand gesture, one of the essential ways for a human to convey information and express
intuitive intention, has a significant degree of differentiation, substantial flexibility, and high …
intuitive intention, has a significant degree of differentiation, substantial flexibility, and high …
Surface EMG-based inter-session gesture recognition enhanced by deep domain adaptation
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity
from a restricted area of the skin by using two dimensional arrays of closely spaced …
from a restricted area of the skin by using two dimensional arrays of closely spaced …
Feature extraction and selection for myoelectric control based on wearable EMG sensors
A Phinyomark, R N. Khushaba, E Scheme - Sensors, 2018 - mdpi.com
Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent
advancements in wearable sensors, wireless communication and embedded technologies …
advancements in wearable sensors, wireless communication and embedded technologies …
Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements
Background Myoelectric pattern recognition systems can decode movement intention to
drive upper-limb prostheses. Despite recent advances in academic research, the …
drive upper-limb prostheses. Despite recent advances in academic research, the …
Deep learning-based artificial vision for grasp classification in myoelectric hands
Objective. Computer vision-based assistive technology solutions can revolutionise the
quality of care for people with sensorimotor disorders. The goal of this work was to enable …
quality of care for people with sensorimotor disorders. The goal of this work was to enable …
Highly conformable stretchable dry electrodes based on inexpensive flex substrate for long-term biopotential (EMG/ECG) monitoring
PF Shahandashti, H Pourkheyrollah… - Sensors and Actuators A …, 2019 - Elsevier
The comfortable, long-term, accurate, and continuous biopotential monitoring is of
paramount importance for biomedical applications. In this respect, dry electrodes are the …
paramount importance for biomedical applications. In this respect, dry electrodes are the …
Current trends and confounding factors in myoelectric control: Limb position and contraction intensity
This manuscript presents a hybrid study of a comprehensive review and a systematic
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …
Interpreting deep learning features for myoelectric control: A comparison with handcrafted features
Existing research on myoelectric control systems primarily focuses on extracting
discriminative characteristics of the electromyographic (EMG) signal by designing …
discriminative characteristics of the electromyographic (EMG) signal by designing …
Toward robust, adaptiveand reliable upper-limb motion estimation using machine learning and deep learning–A survey in myoelectric control
To develop multi-functionalhuman-machine interfaces that can help disabled people
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …