Erik J. Scheme

Biomedical Engineering · 2011–2018

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Biomedical Engineering — 25 citations into it; #5,733 of 10,734 by trust here, #7,854 by citations
• Cellular and Molecular Neuroscience — 23 citations into it; #1,662 of 2,998 by trust here, #2,383 by citations
• Cognitive Neuroscience — 23 citations into it; #6,550 of 10,852 by trust here, #7,600 by citations

Whom Erik J. Scheme trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kevin B. Englehart
2. B. Hudgins
3. Levi J. Hargrove
4. Mohammadreza Asghari Oskoei
5. Adrian D. C. Chan
6. Yonghong Huang
7. Chih-Jen Lin
8. Shlomo S. Sawilowsky
9. Ning Jiang
10. Philip A. Parker

Who trusts Erik J. Scheme overall

1. Xiaolong Zhai
2. Dario Farina
3. Beth Jelfs
4. Ning Jiang
5. Angkoon Phinyomark
6. Manfredo Atzori
7. Rosa H. M. Chan

Papers from Erik J. Scheme's perspective

Ordered by how strongly the researchers Erik J. Scheme trusts endorse each paper. Same corpus, a different order for every researcher.

1. A robust, real-time control scheme for multifunction myoelectric control (IEEE Transactions on Biomedical Engineering)
2. A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses (IEEE Transactions on Biomedical Engineering)
3. Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal (IEEE Transactions on Biomedical Engineering)
4. A Comparison of Surface and Intramuscular Myoelectric Signal Classification (IEEE Transactions on Biomedical Engineering)
5. Continuous myoelectric control for powered prostheses using hidden Markov models (IEEE Transactions on Biomedical Engineering)
6. Targeted Muscle Reinnervation for Real-Time Myoelectric Control of Multifunction Artificial Arms (Journal of the American Medical Association (JAMA))
7. A human-assisting manipulator teleoperated by EMG signals and arm motions (IEEE Trans. Robotics Autom.)
8. Electromyography data for non-invasive naturally-controlled robotic hand prostheses (Scientific Data)
9. LIBSVM: A library for support vector machines
10. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. (Journal of rehabilitation research and development)

Their papers

• Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. (2011) — 966 citations
• Resolving the Limb Position Effect in Myoelectric Pattern Recognition (2011) — 386 citations
• Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors (2018) — 317 citations