A review of current state-of-the-art control methods for lower-limb powered prostheses

R Gehlhar, M Tucker, AJ Young, AD Ames - Annual reviews in control, 2023 - Elsevier
Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb
amputations. While the design of lower-limb prostheses is important, this paper focuses on …

Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use.

E Scheme, K Englehart - Journal of Rehabilitation Research …, 2011 - search.ebscohost.com
Using electromyogram (EMG) signals to control upper-limb prostheses is an important
clinical option, offering a person with amputation autonomy of control by contracting residual …

Self-recalibrating surface EMG pattern recognition for neuroprosthesis control based on convolutional neural network

X Zhai, B Jelfs, RHM Chan, C Tin - Frontiers in neuroscience, 2017 - frontiersin.org
Hand movement classification based on surface electromyography (sEMG) pattern
recognition is a promising approach for upper limb neuroprosthetic control. However …

Electromyogram-based classification of hand and finger gestures using artificial neural networks

KH Lee, JY Min, S Byun - Sensors, 2021 - mdpi.com
Electromyogram (EMG) signals have been increasingly used for hand and finger gesture
recognition. However, most studies have focused on the wrist and whole-hand gestures and …

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 …

[HTML][HTML] Current state of digital signal processing in myoelectric interfaces and related applications

M Hakonen, H Piitulainen, A Visala - Biomedical Signal Processing and …, 2015 - Elsevier
This review discusses the critical issues and recommended practices from the perspective of
myoelectric interfaces. The major benefits and challenges of myoelectric interfaces are …

Continuous locomotion-mode identification for prosthetic legs based on neuromuscular–mechanical fusion

H Huang, F Zhang, LJ Hargrove, Z Dou… - IEEE Transactions …, 2011 - ieeexplore.ieee.org
In this study, we developed an algorithm based on neuromuscular–mechanical fusion to
continuously recognize a variety of locomotion modes performed by patients with …

Study of stability of time-domain features for electromyographic pattern recognition

D Tkach, H Huang, TA Kuiken - Journal of neuroengineering and …, 2010 - Springer
Background Significant progress has been made towards the clinical application of human-
machine interfaces (HMIs) based on electromyographic (EMG) pattern recognition for …

Feasibility of wrist-worn, real-time hand, and surface gesture recognition via sEMG and IMU sensing

S Jiang, B Lv, W Guo, C Zhang, H Wang… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
While most wearable gesture recognition approaches focus on the forearm or fingers, the
wrist may be a more suitable location for practical use. We present the design and validation …

Intelligent EMG pattern recognition control method for upper-limb multifunctional prostheses: advances, current challenges, and future prospects

OW Samuel, MG Asogbon, Y Geng… - Ieee …, 2019 - ieeexplore.ieee.org
Upper-limb amputation imposes significant burden on amputees thereby restricting them
from fully exploring their environments during activities of daily living. The use of intelligent …