Real-time EMG based pattern recognition control for hand prostheses: A review on existing methods, challenges and future implementation

N Parajuli, N Sreenivasan, P Bifulco, M Cesarelli… - Sensors, 2019 - mdpi.com
Upper limb amputation is a condition that significantly restricts the amputees from performing
their daily activities. The myoelectric prosthesis, using signals from residual stump muscles …

Active upper limb prostheses: A review on current state and upcoming breakthroughs

A Marinelli, N Boccardo, F Tessari… - Progress in …, 2023 - iopscience.iop.org
The journey of a prosthetic user is characterized by the opportunities and the limitations of a
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …

Current trends and confounding factors in myoelectric control: Limb position and contraction intensity

E Campbell, A Phinyomark, E Scheme - Sensors, 2020 - mdpi.com
This manuscript presents a hybrid study of a comprehensive review and a systematic
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …

Toward robust, adaptiveand reliable upper-limb motion estimation using machine learning and deep learning–A survey in myoelectric control

T Bao, SQ Xie, P Yang, P Zhou… - IEEE journal of …, 2022 - ieeexplore.ieee.org
To develop multi-functionalhuman-machine interfaces that can help disabled people
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …

Myoelectric control systems for upper limb wearable robotic exoskeletons and exosuits—A systematic review

J Fu, R Choudhury, SM Hosseini, R Simpson, JH Park - Sensors, 2022 - mdpi.com
In recent years, myoelectric control systems have emerged for upper limb wearable robotic
exoskeletons to provide movement assistance and/or to restore motor functions in people …

Toward generalization of sEMG-based pattern recognition: A novel feature extraction for gesture recognition

C Shen, Z Pei, W Chen, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Gesture recognition via surface electromyography (sEMG) has drawn significant attention in
the field of human–computer interaction. An important factor limiting the performance of …

Activities of daily living-based rehabilitation system for arm and hand motor function retraining after stroke

X Song, SS Van De Ven, L Liu… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Most stroke survivors have difficulties completing activities of daily living (ADLs)
independently. However, few rehabilitation systems have focused on ADLs-related training …

Comparing EMG-based human-machine interfaces for estimating continuous, coordinated movements

L Pan, DL Crouch, H Huang - IEEE transactions on neural …, 2019 - ieeexplore.ieee.org
Electromyography (EMG)-based interfaces are trending toward continuous, simultaneous
control with multiple degrees of freedom. Emerging methods range from data-driven …

Recurrent convolutional neural networks as an approach to position-aware myoelectric prosthesis control

HE Williams, AW Shehata, MR Dawson… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Objective: Persons with normal arm function can perform complex wrist and hand
movements over a wide range of limb positions. However, for those with transradial …

Towards resolving the co-existing impacts of multiple dynamic factors on the performance of EMG-pattern recognition based prostheses

MG Asogbon, OW Samuel, Y Geng… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective Mobility of subject (MoS) and muscle contraction force
variation (MCFV) have been shown to individually degrade the performance of multiple …