Faculty profile
Kevin Englehart
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Research
Latest papers
A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN.
Sensors (Basel, Switzerland) · 2020
Regression convolutional neural network for improved simultaneous EMG control.
Journal of neural engineering · 2019 · senior author
On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.
Journal of neural engineering · 2019
Latest funding
- $220,000
Novel Machine Learning Methods for Robust Myoelectric Control
NSERC · 2021 · Principal investigator
- $150,000
Myoelectric Control of Powered Upper Limb Prostheses
NSERC · 2015 · Principal investigator
- $112,372
Haptic Interface for: Computational Motor Control for Better Control of Prosthetic Devices
NSERC · 2014 · Co-investigator
17 publications.
A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN.
Waris A, Zia Ur Rehman M, Niazi IK, Jochumsen M, Englehart K, Jensen W, Haavik H, Kamavuako EN
Regression convolutional neural network for improved simultaneous EMG control.
Ameri A, Akhaee MA, Scheme E, Englehart K
On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.
Waris A, Mendez I, Englehart K, Jensen W, Kamavuako EN
Conventional analysis of trial-by-trial adaptation is biased: Empirical and theoretical support using a Bayesian estimator.
Blustein D, Shehata A, Englehart K, Sensinger J
Real-time, simultaneous myoelectric control using a convolutional neural network.
Ameri A, Akhaee MA, Scheme E, Englehart K
The effect of time on EMG classification of hand motions in able-bodied and transradial amputees.
Waris A, Niazi IK, Jamil M, Gilani O, Englehart K, Jensen W, Shafique M, Kamavuako EN
Do Cost Functions for Tracking Error Generalize across Tasks with Different Noise Levels?
Sensinger J, Aleman-Zapata A, Englehart K
Proceedings of the first workshop on Peripheral Machine Interfaces: going beyond traditional surface electromyography.
Castellini C, Artemiadis P, Wininger M, Ajoudani A, Alimusaj M, Bicchi A, Caputo B, Craelius W, Dosen S, Englehart K, Farina D, Gijsberts A, Godfrey SB, Hargrove L, Ison M, Kuiken T, Marković M, Pilarski PM, Rupp R, Scheme E
Training Strategies for Mitigating the Effect of Proportional Control on Classification in Pattern Recognition Based Myoelectric Control.
Scheme E, Englehart K
High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control.
Daley H, Englehart K, Hargrove L, Kuruganti U
Novel Machine Learning Methods for Robust Myoelectric Control
Principal investigators: Englehart, Kevin
Keywords: electromyogram; human machine interaction; machine learning; pattern recognition; training; learning; adaptation
Myoelectric Control of Powered Upper Limb Prostheses
Principal investigators: Englehart, Kevin
Haptic Interface for: Computational Motor Control for Better Control of Prosthetic Devices
Principal investigators: Sensinger, Jonathon
An intelligent prosthetic socket utilizing novel pressure sensing methods
Principal investigators: Englehart, Kevin
Myoelectric control of powered upper limb prostheses
Principal investigators: Englehart, Kevin
Myoelectric control of powered upper limb prostheses
Principal investigators: Englehart, Kevin
Neuro-biomechanical factors in the design of transfemoral knee prostheses
Principal investigators: McGibbon, Chris
Keywords: Biomechanics; Knee Joint Motion; Mobility; Neuro-Control Of Movement; Transfemoral Knee Prosthesis
Myoelectric signal source separation for prosthetic control
Principal investigators: Englehart, Kevin
Myoelectric signal processing
Principal investigators: Englehart, Kevin
Myoelectric signal processing
Principal investigators: Englehart, Kevin
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Erik Scheme and Kevin Englehart: 5 shared papers
- Jonathon Sensinger and Kevin Englehart: 2 shared papers
- Electrical and Computer Engineering
Co-authors at University of New Brunswick, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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