Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis
Strahinja Došen, Marko Marković, Kelef Somer, et al.
Journal of NeuroEngineering and Rehabilitation (2015) Vol. 12, Iss. 1
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control
Jonathon W. Sensinger, Strahinja Došen
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 166
The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis
Marko Marković, Meike A. Schweisfurth, Leonard F. Engels, et al.
Journal of NeuroEngineering and Rehabilitation (2018) Vol. 15, Iss. 1
Open Access | Times Cited: 119
Electrotactile EMG feedback improves the control of prosthesis grasping force
Meike A. Schweisfurth, Marko Marković, Strahinja Došen, et al.
Journal of Neural Engineering (2016) Vol. 13, Iss. 5, pp. 056010-056010
Closed Access | Times Cited: 106
Active upper limb prostheses: a review on current state and upcoming breakthroughs
Andrea Marinelli, Nicolò Boccardo, Federico Tessari, et al.
Progress in Biomedical Engineering (2022) Vol. 5, Iss. 1, pp. 012001-012001
Open Access | Times Cited: 45
Virtual/Augmented Reality for Rehabilitation Applications Using Electromyography as Control/Biofeedback: Systematic Literature Review
Cinthya Lourdes Toledo-Peral, G. Vega-Martínez, Jorge A. Mercado-Gutiérrez, et al.
Electronics (2022) Vol. 11, Iss. 14, pp. 2271-2271
Open Access | Times Cited: 39
Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees
Matija Štrbac, Milica Isaković, Minja Belić, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2017) Vol. 25, Iss. 11, pp. 2133-2145
Closed Access | Times Cited: 85
Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control
Arvind Gautam, Madhuri Panwar, Archana Wankhede, et al.
IEEE Journal of Translational Engineering in Health and Medicine (2020) Vol. 8, pp. 1-12
Open Access | Times Cited: 56
Multichannel haptic feedback unlocks prosthetic hand dexterity
A. Moaed, Joseph Ingicco, Douglas T. Hutchinson, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 32
Current status and clinical perspectives of extended reality for myoelectric prostheses: review
Wei Li, Ping Shi, Sujiao Li, et al.
Frontiers in Bioengineering and Biotechnology (2024) Vol. 11
Open Access | Times Cited: 6
Myocontrol is closed-loop control: incidental feedback is sufficient for scaling the prosthesis force in routine grasping
Marko Marković, Meike A. Schweisfurth, Leonard F. Engels, et al.
Journal of NeuroEngineering and Rehabilitation (2018) Vol. 15, Iss. 1
Open Access | Times Cited: 58
Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand
Francesco Clemente, Strahinja Došen, Luca Lonini, et al.
IEEE Transactions on Human-Machine Systems (2016) Vol. 47, Iss. 4, pp. 583-589
Closed Access | Times Cited: 52
GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses
Marko Marković, Hemanth Karnal, Bernhard Graimann, et al.
Journal of Neural Engineering (2017) Vol. 14, Iss. 3, pp. 036007-036007
Closed Access | Times Cited: 52
Analysis of Man-Machine Interfaces in Upper-Limb Prosthesis: A Review
José Cairo Silva Ribeiro, Francisco Mota, Tarique da Silveira Cavalcante, et al.
Robotics (2019) Vol. 8, Iss. 1, pp. 16-16
Open Access | Times Cited: 49
Improving internal model strength and performance of prosthetic hands using augmented feedback
Ahmed W. Shehata, Leonard F. Engels, Marco Controzzi, et al.
Journal of NeuroEngineering and Rehabilitation (2018) Vol. 15, Iss. 1
Open Access | Times Cited: 47
Immersive augmented reality system for the training of pattern classification control with a myoelectric prosthesis
Alexander Boschmann, D. Neuhaus, Sarah Vogt, et al.
Journal of NeuroEngineering and Rehabilitation (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 32
Adaptation to random and systematic errors: Comparison of amputee and non-amputee control interfaces with varying levels of process noise
Reva E. Johnson, Konrad P. Körding, Levi J. Hargrove, et al.
PLoS ONE (2017) Vol. 12, Iss. 3, pp. e0170473-e0170473
Open Access | Times Cited: 37
When Less Is More – Discrete Tactile Feedback Dominates Continuous Audio Biofeedback in the Integrated Percept While Controlling a Myoelectric Prosthetic Hand
Leonard F. Engels, Ahmed W. Shehata, Erik Scheme, et al.
Frontiers in Neuroscience (2019) Vol. 13
Open Access | Times Cited: 33
Audible Feedback Improves Internal Model Strength and Performance of Myoelectric Prosthesis Control
Ahmed W. Shehata, Erik Scheme, Jonathon W. Sensinger
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 32
Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis
Meike A. Wilke, Christian Niethammer, Britta Meyer, et al.
Journal of NeuroEngineering and Rehabilitation (2019) Vol. 16, Iss. 1
Open Access | Times Cited: 31
The effect of calibration parameters on the control of a myoelectric hand prosthesis using EMG feedback
Jack Tchimino, Marko Marković, Jakob Lund Dideriksen, et al.
Journal of Neural Engineering (2021) Vol. 18, Iss. 4, pp. 046091-046091
Open Access | Times Cited: 26
A compact system for simultaneous stimulation and recording for closed-loop myoelectric control
Martin A. Garenfeld, Nikola Jorgovanović, V. Ilić, et al.
Journal of NeuroEngineering and Rehabilitation (2021) Vol. 18, Iss. 1
Open Access | Times Cited: 23
Nonlinear Mapping From EMG to Prosthesis Closing Velocity Improves Force Control With EMG Biofeedback
Filip Gasparic, Nikola Jorgovanović, Christian Höfer, et al.
IEEE Transactions on Haptics (2023) Vol. 16, Iss. 3, pp. 379-390
Closed Access | Times Cited: 9
Examination of Biofeedback to Support the Use of Upper-Extremity Exoskeletons Under Proportional Myoelectric Control
Xiangyu Peng, Leia Stirling
IEEE Transactions on Medical Robotics and Bionics (2024) Vol. 6, Iss. 2, pp. 662-673
Closed Access | Times Cited: 3
EMG Versus Torque Control of Human–Machine Systems: Equalizing Control Signal Variability Does not Equalize Error or Uncertainty
Reva E. Johnson, Konrad P. Körding, Levi J. Hargrove, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2016) Vol. 25, Iss. 6, pp. 660-667
Open Access | Times Cited: 29
Stiffness-Estimation-Based Grasping Force Fuzzy Control for Underactuated Prosthetic Hands
Yi Zhang, Xiaolei Xu, Ruiheng Xia, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 28, Iss. 1, pp. 140-151
Closed Access | Times Cited: 14
Page 1 - Next Page

Scroll to top