Research Topics
| K EnglehartSummaryAffiliation: University of New Brunswick Country: Canada Publications
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Detail Information
Publications
A robust, real-time control scheme for multifunction myoelectric controlKevin Englehart
Department of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, NB E3B5A3, Canada
IEEE Trans Biomed Eng 50:848-54. 2003..Finally, minimal storage capacity is required, which is an important factor in embedded control systems...
Classification of the myoelectric signal using time-frequency based representationsK Englehart
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, Canada
Med Eng Phys 21:431-8. 1999....
A wavelet-based continuous classification scheme for multifunction myoelectric controlK Englehart
Department of Electrical and Computer Engineering and the Institute of Biomedical Engineering, University of New Brunswick, Fredericton, Canada
IEEE Trans Biomed Eng 48:302-11. 2001..Although in its preliminary stages of development, this scheme promises a more natural and efficient means of myoelectric control than one based on discrete, transient bursts of activity...
A control system for a powered prosthesis using positional and myoelectric inputs from the shoulder complexY Losier
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB Canada
Conf Proc IEEE Eng Med Biol Soc 2007:6138-41. 2007..This work is another important step in the development of hybrid systems that will enable simultaneous control of multiple degrees of freedom used for reaching tasks in a prosthetic limb...
Principal components analysis preprocessing to reduce controller delays in pattern recognition based myoelectric controlL Hargrove
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB Canada
Conf Proc IEEE Eng Med Biol Soc 2007:6512-5. 2007..This tunes the pattern recognition classifier to better discriminate the test motions. Using this preprocessing step, MES analysis windows may be cut from 256 ms to 128 ms without affecting the classification accuracy...
The effect of electrode displacements on pattern recognition based myoelectric controlL Hargrove
Inst of Biomed Eng, New Brunswick Univ, Fredericton, NB, Canada
Conf Proc IEEE Eng Med Biol Soc 1:2203-6. 2006..The effects of electrode displacement can be mitigated by using a training set of data which consists of patterns detected over a range of plausible displacement locations to train the control system...
Myoelectric signal processing for control of powered limb prosthesesP Parker
Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, 15 Dineen Drive, P O Box 4400, Fredericton, NB, Canada E3B 5A3
J Electromyogr Kinesiol 16:541-8. 2006..The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon...
Myo-electric signals to augment speech recognitionA D Chan
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, Canada
Med Biol Eng Comput 39:500-4. 2001..7% and 10.4%. The results demonstrate that there is excellent potential for using surface myo-electric signals to enhance the performance of a conventional speech-recognition system...
Pattern recognition of single and combined motions from the shoulder complexV R Buerkle
Inst of Biomed Eng, New Brunswick Univ, Fredericton, NB, Canada
Conf Proc IEEE Eng Med Biol Soc 1:3419-22. 2006..However, as the level of limb loss increases so does the need for functional replacement. This study investigates pattern recognition concepts for independent control of an artificial shoulder...
A real-time pattern recognition based myoelectric control usability study implemented in a virtual environmentL Hargrove
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB Canada
Conf Proc IEEE Eng Med Biol Soc 2007:4842-5. 2007..Additionally, results indicate that a clinically-supported classifier training approach (inclusion of the transient potion of contraction signals) may reduce classification accuracy but increase real-time performance...
Improved phoneme-based myoelectric speech recognitionQuan Zhou
Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
IEEE Trans Biomed Eng 56:2016-23. 2009..An average word classification accuracy of 98.533% is achieved over six subjects. The system offers dramatically improved accuracy when expanding a vocabulary, offering promise for robust large-vocabulary myoelectric speech recognition...
A comparison of surface and intramuscular myoelectric signal classificationLevi J Hargrove
Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, P O Box 4400, Fredericton, NB E3B 5A3, Canada
IEEE Trans Biomed Eng 54:847-53. 2007..Impressive classification accuracy (97%) could be achieved by optimally selecting only three channels of surface MES...
A novel simulation model for the motor unit innervation processNing Jiang
Institute of Biomedical Engineering, and Department of Electrical and Computer Engineering, University of New Brunswick, Canada
Conf Proc IEEE Eng Med Biol Soc 3:2993-6. 2005..Some simulation results are presented and possible extensions of the model are discussed...
The Motor Unit Innervation Process Correlation and Its Effects on EMG ApplicationsNing Jiang
Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, Canada
Conf Proc IEEE Eng Med Biol Soc 4:4239-42. 2005..Simulation results show that MUIP correlation may compromise the assumption of uncorrelated MUAPTs (depending on recruitment level), and MUIP correlation has a downwards spectrum compression effect on the power spectrum of EMG...
Improving myoelectric pattern recognition positional robustness using advanced training protocolsE Scheme
Institute of Biomedical Engineering at the University of New Brunswick, Fredericton, NB, Canada
Conf Proc IEEE Eng Med Biol Soc 2011:4828-31. 2011..It is shown that training with dynamic activities can greatly improve positional robustness for both static and dynamic tasks, without requiring a complex and lengthy training session...
Examining the adverse effects of limb position on pattern recognition based myoelectric controlE Scheme
Institute of Biomedical Engineering at the University of New Brunswick, Fredericton, Canada
Conf Proc IEEE Eng Med Biol Soc 2010:6337-40. 2010..In this work, we demonstrate that variations in limb position after training can have a substantial impact on the robustness of myoelectric pattern recognition...
Hidden Markov model classification of myoelectric signals in speechA D C Chan
Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, Canada
IEEE Eng Med Biol Mag 21:143-6. 2002
