| Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted U Côté-Allard, E Campbell, A Phinyomark, F Laviolette, B Gosselin, ... Highlights from Frontiers in Bioengineering and Biotechnology in 2020, 2021 | 93 | 2021 |
| Current trends and confounding factors in myoelectric control: Limb position and contraction intensity E Campbell, A Phinyomark, E Scheme Sensors 20 (6), 1613, 2020 | 93 | 2020 |
| Surface electromyography (EMG) signal processing, classification, and practical considerations A Phinyomark, E Campbell, E Scheme Biomedical Signal Processing: Advances in Theory, Algorithms and …, 2020 | 79* | 2020 |
| Feature extraction and selection for pain recognition using peripheral physiological signals E Campbell, A Phinyomark, E Scheme Frontiers in neuroscience 13, 437, 2019 | 49 | 2019 |
| 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 | 33 | 2019 |
| Deep cross-user models reduce the training burden in myoelectric control E Campbell, A Phinyomark, E Scheme Frontiers in Neuroscience 15, 657958, 2021 | 29 | 2021 |
| 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 | 19 | 2019 |
| 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 | 15 | 2020 |
| 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 | 11 | 2020 |
| Differences in Perspective on Inertial Measurement Unit Sensor Integration in Myoelectric Control E Campbell, A Phinyomark, E Scheme MEC20: Myoelectric Controls Symposium, 2020 | 5 | 2020 |
| Novel wearable HD-EMG sensor with shift-robust gesture recognition using deep learning F Chamberland, É Buteau, S Tam, E Campbell, A Mortazavi, E Scheme, ... IEEE Transactions on Biomedical Circuits and Systems, 2023 | 2 | 2023 |
| LibEMG: An Open Source Library to Facilitate the Exploration of Myoelectric Control E Eddy, E Campbell, A Phinyomark, S Bateman, E Scheme IEEE Access, 2023 | 2 | 2023 |
| Generalizing Upper Limb Force Modeling with Transfer Learning: A Multimodal Approach Using EMG and IMU for New Users and Conditions G Hajian, E Campbell, M Ansari, E Morin, A Etemad, K Englehart, ... IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024 | 1 | 2024 |
| On-Demand Myoelectric Control Using Wake Gestures to Eliminate False Activations During Activities of Daily Living E Eddy, E Campbell, S Bateman, E Scheme arXiv preprint arXiv:2402.10050, 2024 | | 2024 |
| Live Demonstration: A fully embedded adaptive real-time hand gesture classifier leveraging HD-sEMG and deep learning X Isabel, T Labbé, F Chamberland, É Buteau, E Campbell, U Côté-Allard, ... 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-1, 2023 | | 2023 |
| Leveraging Task-Specific Context to Improve Unsupervised Adaptation for Myoelectric Control E Eddy, E Campbell, S Bateman, E Scheme 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2023 | | 2023 |
| Data-driven approaches to reducing the training burden in pattern recognition based myoelectric control ED Campbell University of New Brunswick, 2020 | | 2020 |
Erik SchemeAssociate Director, Institute of Biomedical EngineeringПодтвержден адрес электронной почты в домене unb.ca
