latentnotion.com Adaptive systems

Curriculum Vitae

Evan Campbell

Electrical engineering researcher working across adaptive myoelectric control, machine learning, and human–machine interaction.

Google Scholar

01

Publications

  1. Campbell, E., Eddy, E., Scheme, E..

    Transformer-based Context-Informed Incremental learning with sDTW Alignment Unlocks Fast and Precise Regression-Based Myoelectric Control.

    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol 34, No 1, Apr 2026

    DOI: 10.1109/TNSRE.2026.3685074

  2. Campbell, E., Egle, F., Oßwald, M., Côté-Allard, U., Pilarski, P., Boccardo, N., Meattini, R., Vujaklija, I., Hargrove, L., Canepa, M., Eddy, E., Del Vecchio, A., Castellini, C., Scheme, E..

    (Un)supervised (Co)adaptation via Incremental Learning for Myoelectric Control: Motivation, Review, and Future Directions.

    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol 33, No 1, Aug 2025, pp. 3565

    DOI: 10.1109/TNSRE.2025.3602397

  3. Eddy, E., Campbell, E., Morrell, C., Williams, H., Bateman, S., Scheme, E..

    Raising the standard: an open source benchmarking platform and data repository to accelerate myoelectric control research.

    Machine Learning: Health Vol 1, No 1, Jul 2025, pp. 1

    DOI: 10.1088/3049-477X/ade549

  4. Morrell, C., Campbell, E., Eddy, E., Scheme, E..

    Context-Informed Incremental Learning Improves Throughput and Reduces Drift in Regression-Based Myoelectric Control.

    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol 33, No 1, May 2025, pp. 1841

    DOI: 10.1109/TNSRE.2025.3567245

  5. Eddy, E., Campbell, E., Bateman, S., Scheme, E..

    EMG-based wake gestures eliminate false activations during out-of-set activities of daily living: an online myoelectric control study.

    Journal of Neural Engineering Vol 22, No 1, Jan 2025, pp. 1

    DOI: 10.1088/1741-2552/ada4df

  6. Campbell, E., Eddy, E., Isabel, X., Bateman, S., Gosselin, B., Côté-Allard, U., Scheme, E..

    Screen Guided Training Does Not Capture Goal-Oriented Behaviours: Learning Myoelectric Control Mappings From Scratch Using Context Informed Incremental Learning.

    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol 33, No 1, Dec 2024, pp. 332

    DOI: 10.1109/TNSRE.2024.3518059

  7. Eddy, E., Campbell, E., Bateman, S., Scheme, E..

    Big data in myoelectric control: large multi-user models enable robust zero-shot EMG-based discrete gesture recognition.

    Frontiers in Bioengineering and Biotechnology Vol 12, No 1, Sep 2024, pp. 1

    DOI: 10.3389/fbioe.2024.1463377

  8. Eddy, E., Campbell, E., Côté-Allard, U., Bateman, S., Scheme, E..

    Discrete Gesture Recognition Using Multimodal PPG, IMU, and Single-Channel EMG Recorded at the Wrist.

    IEEE Sensors Letters Vol 8, No 9, Sep 2024, pp. 1

    DOI: 10.1109/LSENS.2024.3447240

  9. Eddy, E., Campbell, E., Bateman, S., Scheme, E..

    Understanding the influence of confounding factors in myoelectric control for discrete gesture recognition.

    Journal of Neural Engineering Vol 21, No 3, May 2024, pp. 1

    DOI: 10.1088/1741-2552/ad4915

  10. Campbell, E., Eddy, E., Bateman, S., Côté-Allard, U., Scheme, E..

    Context-informed incremental learning improves both the performance and resilience of myoelectric control.

    Journal of NeuroEngineering and Rehabilitation Vol 21, No 1, May 2024, pp. 70

    DOI: 10.1186/s12984-024-01355-4

  11. Hajian, G., Campbell, E., Ansari, M., Morin, E., Etemad, A., Englehart, K., Scheme, E..

    Generalizing upper limb force modeling with transfer learning: a multimodal approach using emg and imu for new users and conditions.

    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol 32, No 1, Jan 2024, pp. 391

    DOI: 10.1109/TNSRE.2024.3351829

  12. Chamberland, F., Buteau, E., Tam, S., Campbell, E., Mortazavi, A., Scheme, E., Fortier, P., Boukadoum, M., Campeau-Lecours, A., Gosselin, B..

    Novel wearable HD-EMG sensor with shift-robust gesture recognition using deep learning.

    IEEE Transactions on Biomedical Circuits and Systems Vol 17, No 5, Sep 2023, pp. 968

    DOI: 10.1109/TBCAS.2023.3314053

  13. Eddy, E., Campbell, E., Phinyomark, A., Bateman, S., Scheme, E..

    LibEMG: an open source library to facilitate the exploration of myoelectric control.

    IEEE Access Vol 11, Aug 2023, pp. 87380

    DOI: 10.1109/ACCESS.2023.3304544

  14. Campbell, E., Phinyomark, A., Scheme, E..

    Deep cross-user models reduce the training burden in myoelectric control.

    Frontiers in Neuroscience Vol 15, May 2021, pp. 1

    DOI: 10.3389/fnins.2021.657958

  15. Campbell, E., Phinyomark, A., Scheme, E..

    Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity.

    Sensors Vol 20, No 6, Mar 2020, pp. 333

    DOI: 10.3390/s20061613

  16. Phinyomark, A., Campbell, E., Scheme, E..

    Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations.

    Biomedical Signal Processing - Advances in Theory, Algorithms, and Applications (Springer) pp. 3–29, 2020

    DOI: 10.1007/978-981-13-9097-5_1

  17. Côté-Allard, U., Campbell, E., Phinyomark, A., Laviolette, F., Gosselin, B., Scheme, E..

    Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted Features.

    Frontiers in Bioengineering and Biotechnology Vol 8, Mar 2020

    DOI: 10.3389/fbioe.2020.00158

  18. Campbell, E., Phinyomark, A., Scheme, E..

    Feature Extraction and Selection for Pain Recognition Using Peripheral Physiological Signals.

    Frontiers in Neuroscience Vol 13, No 437, May 2019

    DOI: 10.3389/fnins.2019.00437

02

Conference Presentations

  1. Eddy, E., Campbell, E., Scheme, E., Bateman, S., Casiez, G..

    TFTune: Creation and Personalization of Pointing Transfer Functions Using Reinforcement Learning.

    Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems April 13, 2026

    DOI: 10.1145/3772318.3790291

  2. Eddy, E., Campbell, E., Scheme, E., Bateman, S...

    Open, Accurate, and Calibration-Free Muscle-Computer Interfaces.

    Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems April 13, 2026

    DOI: 10.1145/3772318.3790689

  3. Gagné, G., Azad, A., Labbé, T., Campbell, E., Isabel, X., Scheme, E., Côté-Allard, U., Gosselin, B..

    Context Informed Incremental Learning Improves Myoelectric Control Performance in Virtual Reality Object Manipulation Tasks.

    47th Annual International Conference of the IEEE EMBS, Copenhagen, Denmark July 14–17, 2025

    DOI: 10.48550/arXiv.2505.06064

  4. Eddy, E., Campbell, E., Bateman, S., Scheme, E..

    Human-Machine Interaction Using Discrete Myoelectric Control: Contrastive Learning Reduces False Activations During Activities of Daily Living.

    10th IEEE RAS/EMBS BioRob, Heidelberg, Germany Sep 1–4, 2024

    DOI: 10.1109/BioRob60516.2024.10719934

  5. Morrell, C., Campbell, E., Scheme, E..

    Exploring user compliance in the training of regression-based myoelectric control.

    Myoelectric Controls Symposium (MEC), Fredericton, Canada Aug 15, 2024

    DOI: 10.57922/mec.2507

  6. Chamberland, F., Isabel, X., Campbell, E., Gagné, G., Gosselin, B., Scheme, E., Gagnon-Turcotte, G., Côté-Allard, U..

    BioPoint: Single-site, Multi-sensor Compound Gesture Recognition.

    Myoelectric Controls Symposium (MEC), Fredericton, Canada Aug 15, 2024

    DOI: 10.57922/mec.2505

  7. Campbell, E., Eddy, E., Côté-Allard, U., Scheme, E..

    Improving User-in-the-Loop Myoelectric Control Using Context Informed Incremental Learning.

    Myoelectric Controls Symposium (MEC), Fredericton, Canada Aug 15, 2024

    DOI: 10.57922/mec.2498

  8. Isabel, X., Campbell, E., Olivier, L., Gagné, G., Scheme, E., Côté-Allard, U., Gagnon-Turcotte, G..

    BioPoint: Enhancing Human-Computer Interaction through Single-Site, Multi-Sensor Gesture Recognition.

    46th Annual International Conference of the IEEE EMBS, Orlando, USA July 15, 2024

    DOI: 10.1109/EMBC53108.2024.10781656

  9. Eddy, E., Campbell, E., Bateman, S., Scheme, E..

    Leveraging task-specific context to improve unsupervised adaptation for myoelectric control.

    IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, USA Oct 1, 2023

    DOI: 10.1109/SMC53992.2023.10394393

  10. Campbell, E., Chang, J., Phinyomark, A., Scheme, E..

    A Comparison Of Amputee And Able-Bodied Inter-Subject Variability In Myoelectric Control.

    Myoelectric Controls Symposium MEC ’20, Fredericton, Canada (Online) Aug 2020

    DOI: arXiv:2003.03481

  11. Campbell, E., Phinyomark, A., Scheme, E..

    Differences In Perspective On Inertial Measurement Unit Sensor Integration In Myoelectric Control.

    Myoelectric Controls Symposium MEC ’20, Fredericton, Canada (Online) Aug 2020

    DOI: arXiv:2003.03424

  12. Campbell, E., Cameron, J., Scheme, E..

    Feasibility of Data-driven EMG Signal Generation using a Deep Generative Model.

    42nd Annual International Conference of the IEEE EMBS, Montreal, Canada July 20–24, 2020

    DOI: 10.1109/EMBC44109.2020.9176072

  13. Campbell, E., Phinyomark, A., Scheme, E..

    Linear Discriminant Analysis with Bayesian Risk Parameters for Myoelectric Control.

    7th IEEE Global Conference on Signal and Information Processing, Ottawa, Canada Nov 11–14, 2019

    DOI: 10.1109/GlobalSIP45357.2019.8969237

  14. Campbell, E., Phinyomark, A., Al-Timemy, A., Khushaba, R., Petri, G., Scheme, E..

    Differences in EMG Feature Space between Able-Bodied and Amputee Subjects for Myoelectric Control.

    IEEE Conference on Neural Engineering, San Francisco, USA Mar 20–23, 2019

    DOI: 10.1109/NER.2019.8717161

03

Workshops Hosted

  1. Scheme, E.; Campbell, E.; Eddy, E..

    From Prosthetics to Human-Computer Interactions: Advances and Trends in Myoelectric Control; Exploring EMG-Driven Engineering Solutions with the Delsys API.

    Delsys Webinar, July 16, 2025

    https://delsys.com/event/webinar-emg-driven-engineering-solutions/

  2. Egle, F.; Campbell, E.; Oßwald, M..

    WS10: (Co-)Adaptive (Un-)Supervised Learning for Myocontrol.

    ICNR 2024, November 20, 2024

    https://2024.icneurorehab.org/workshops/

  3. Scheme, E.; Campbell, E.; Eddy, E.; Morrell, C..

    LibEMG Workshop: A New Open Source Library for Developing Myoelectric Interfaces and Conducting Myoelectric Control Research.

    Myoelectric Controls Symposium (MEC), Aug 11, 2024

    https://www.unb.ca/ibme/mec/index.html

latentnotion.com

Research notes on adaptive learning systems and the people who use them.

© 2025 Evan Campbell. All content on this site may be freely reused, remixed, or adapted, provided that reasonable credit is given to the original author.