Eric M. Schearer

412 total citations
32 papers, 263 citations indexed

About

Eric M. Schearer is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Rehabilitation. According to data from OpenAlex, Eric M. Schearer has authored 32 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Biomedical Engineering, 18 papers in Cognitive Neuroscience and 10 papers in Rehabilitation. Recurrent topics in Eric M. Schearer's work include Muscle activation and electromyography studies (25 papers), EEG and Brain-Computer Interfaces (15 papers) and Stroke Rehabilitation and Recovery (10 papers). Eric M. Schearer is often cited by papers focused on Muscle activation and electromyography studies (25 papers), EEG and Brain-Computer Interfaces (15 papers) and Stroke Rehabilitation and Recovery (10 papers). Eric M. Schearer collaborates with scholars based in United States, Italy and Philippines. Eric M. Schearer's co-authors include Marcia K. O’Malley, Eric J. Perreault, Kevin Lynch, Matthew C. Tresch, Yu-Wei Liao, William D. Memberg, Robert F. Kirsch, Craig G. McDonald, John R. Schultz and Antonie J. van den Bogert and has published in prestigious journals such as PLoS ONE, Experimental Neurology and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

In The Last Decade

Eric M. Schearer

30 papers receiving 260 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eric M. Schearer United States 10 194 127 115 61 49 32 263
Christian A. Cousin United States 11 275 1.4× 121 1.0× 108 0.9× 118 1.9× 22 0.4× 46 376
Nicholas Kirsch United States 12 417 2.1× 149 1.2× 92 0.8× 118 1.9× 82 1.7× 22 459
R. Davoodi United States 9 323 1.7× 118 0.9× 160 1.4× 95 1.6× 99 2.0× 18 395
T. Fuhr Germany 6 289 1.5× 76 0.6× 105 0.9× 98 1.6× 22 0.4× 14 335
Naji Alibeji United States 12 441 2.3× 169 1.3× 98 0.9× 119 2.0× 100 2.0× 21 499
Kai Gui China 9 349 1.8× 192 1.5× 173 1.5× 77 1.3× 11 0.2× 15 475
Jiping He United States 6 218 1.1× 160 1.3× 48 0.4× 37 0.6× 114 2.3× 13 422
Rahman Davoodi United States 10 247 1.3× 71 0.6× 196 1.7× 107 1.8× 13 0.3× 25 310
Victor H. Duenas United States 11 267 1.4× 128 1.0× 82 0.7× 108 1.8× 24 0.5× 42 336
Guillaume Durandau Netherlands 10 525 2.7× 186 1.5× 177 1.5× 65 1.1× 29 0.6× 22 566

Countries citing papers authored by Eric M. Schearer

Since Specialization
Citations

This map shows the geographic impact of Eric M. Schearer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric M. Schearer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric M. Schearer more than expected).

Fields of papers citing papers by Eric M. Schearer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric M. Schearer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric M. Schearer. The network helps show where Eric M. Schearer may publish in the future.

Co-authorship network of co-authors of Eric M. Schearer

This figure shows the co-authorship network connecting the top 25 collaborators of Eric M. Schearer. A scholar is included among the top collaborators of Eric M. Schearer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eric M. Schearer. Eric M. Schearer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Schearer, Eric M., et al.. (2024). Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 956–966. 7 indexed citations
4.
Schearer, Eric M., et al.. (2024). Global system errors to simultaneously improve the identification of subsystems with mixed data Gaussian process regression. Machine Learning Science and Technology. 5(2). 25051–25051. 1 indexed citations
5.
Schearer, Eric M., et al.. (2023). Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements. Frontiers in Neurorobotics. 17. 1127783–1127783. 15 indexed citations
6.
Bogert, Antonie J. van den, et al.. (2023). Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 2246–2256. 4 indexed citations
7.
Slifkin, Andrew B., et al.. (2022). Controlling an effector with eye movements: The effect of entangled sensory and motor responsibilities. PLoS ONE. 17(2). e0263440–e0263440. 1 indexed citations
8.
Schearer, Eric M., et al.. (2021). Physically Disabled Students in Summer Undergraduate Research Environments. IEEE Transactions on Education. 65(2). 156–166. 3 indexed citations
9.
Schearer, Eric M., et al.. (2020). Predicting functional force production capabilities of upper extremity functional electrical stimulation neuroprostheses: a proof of concept study. Journal of Neural Engineering. 17(1). 16051–16051. 2 indexed citations
10.
Schearer, Eric M., et al.. (2020). A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance. Experimental Neurology. 328. 113274–113274. 38 indexed citations
11.
Schearer, Eric M., et al.. (2020). Model Learning for Control of a Paralyzed Human Arm with Functional Electrical Stimulation. EngagedScholarship @ Cleveland State University (Cleveland State University). 10148–10154. 11 indexed citations
12.
Schearer, Eric M., et al.. (2019). Developing a Quasi-Static Controller for a Paralyzed Human Arm: A Simulation Study. PubMed. 2019. 1153–1158. 2 indexed citations
13.
Schearer, Eric M., et al.. (2018). Holding Static Arm Configurations With Functional Electrical Stimulation: A Case Study. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(10). 2044–2052. 17 indexed citations
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Schearer, Eric M., et al.. (2017). Wearable force/torque sensor for updating models of paralyzed arms. 1–1. 1 indexed citations
16.
Schearer, Eric M., Yu-Wei Liao, Eric J. Perreault, et al.. (2016). Semiparametric Identification of Human Arm Dynamics for Flexible Control of a Functional Electrical Stimulation Neuroprosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 24(12). 1405–1415. 20 indexed citations
17.
Schearer, Eric M., Yu-Wei Liao, Eric J. Perreault, et al.. (2015). Evaluation of a semi-parametric model for high-dimensional FES control. EngagedScholarship @ Cleveland State University (Cleveland State University). 304–307. 7 indexed citations
18.
Schearer, Eric M., et al.. (2014). Multi-muscle FES control of the human arm for interaction tasks—Stabilizing with muscle co-contraction and postural adjustment: A simulation study. EngagedScholarship @ Cleveland State University (Cleveland State University). 17. 2134–2139. 3 indexed citations
19.
Liao, Yu-Wei, et al.. (2013). Modeling open-loop stability of a human arm driven by a functional electrical stimulation neuroprosthesis. PubMed. 2013. 3598–601. 6 indexed citations
20.
Schearer, Eric M., Yu-Wei Liao, Eric J. Perreault, Matthew C. Tresch, & Kevin Lynch. (2012). Optimal sampling of recruitment curves for functional electrical stimulation control. PubMed. 2012. 329–332. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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