Evan Campbell
Title
Cited by
Cited by
Year
Surface electromyography (EMG) signal processing, classification, and practical considerations
A Phinyomark, E Campbell, E Scheme
Biomedical signal processing, 3-29, 2020
172020
Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted
U Côté-Allard, E Campbell, A Phinyomark, F Laviolette, B Gosselin, ...
Machine Learning Approaches to Human Movement Analysis, 2021
152021
Current trends and confounding factors in myoelectric control: Limb position and contraction intensity
E Campbell, A Phinyomark, E Scheme
Sensors 20 (6), 1613, 2020
112020
Differences in EMG feature space between able-bodied and amputee subjects for myoelectric control
E Campbell, A Phinyomark, AH Al-Timemy, RN Khushaba, G Petri, ...
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 33-36, 2019
92019
Feature extraction and selection for pain recognition using peripheral physiological signals
E Campbell, A Phinyomark, E Scheme
Frontiers in neuroscience 13, 437, 2019
92019
Linear Discriminant Analysis with Bayesian Risk Parameters for Myoelectric Control
E Campbell, A Phinyomark, E Scheme
2019 IEEE Global Conference on Signal and Information Processing, 2019
42019
A Comparison of Amputee and Able-Bodied Inter-Subject Variability in Myoelectric Control
E Campbell, J Chang, A Phinyomark, E Scheme
MEC20: Myoelectric Controls Symposium, 2020
22020
Differences in Perspective on Inertial Measurement Unit Sensor Integration in Myoelectric Control
E Campbell, A Phinyomark, E Scheme
MEC20: Myoelectric Controls Symposium, 2020
22020
Feasibility of Data-driven EMG Signal Generation using a Deep Generative Model
E Campbell, JAD Cameron, E Scheme
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
2020
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