Eric T. Wolbrecht

2.2k total citations
61 papers, 1.6k citations indexed

About

Eric T. Wolbrecht is a scholar working on Rehabilitation, Biomedical Engineering and Ocean Engineering. According to data from OpenAlex, Eric T. Wolbrecht has authored 61 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Rehabilitation, 27 papers in Biomedical Engineering and 16 papers in Ocean Engineering. Recurrent topics in Eric T. Wolbrecht's work include Stroke Rehabilitation and Recovery (34 papers), Muscle activation and electromyography studies (25 papers) and Underwater Vehicles and Communication Systems (16 papers). Eric T. Wolbrecht is often cited by papers focused on Stroke Rehabilitation and Recovery (34 papers), Muscle activation and electromyography studies (25 papers) and Underwater Vehicles and Communication Systems (16 papers). Eric T. Wolbrecht collaborates with scholars based in United States, Spain and Italy. Eric T. Wolbrecht's co-authors include David J. Reinkensmeyer, J.E. Bobrow, Vicky Chan, Steven C. Cramer, Morgan L. Ingemanson, Justin B. Rowe, Dean B. Edwards, Richard A. Smith, Alba Pérez-Gracia and Joel C. Perry and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Neurology.

In The Last Decade

Eric T. Wolbrecht

58 papers receiving 1.5k 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 T. Wolbrecht United States 22 1.1k 869 384 315 175 61 1.6k
Neville Hogan United States 20 934 0.9× 1.4k 1.6× 727 1.9× 299 0.9× 192 1.1× 62 2.1k
Jerome J. Palazzolo United States 10 1.1k 1.0× 886 1.0× 460 1.2× 365 1.2× 211 1.2× 11 1.5k
Elena Bergamini Italy 22 139 0.1× 652 0.8× 71 0.2× 85 0.3× 204 1.2× 64 1.6k
D. Roetenberg Netherlands 12 126 0.1× 699 0.8× 136 0.4× 34 0.1× 82 0.5× 16 1.8k
F. Vecchi Italy 19 542 0.5× 1.3k 1.5× 363 0.9× 84 0.3× 25 0.1× 43 1.6k
S. Farokh Atashzar United States 26 303 0.3× 1.0k 1.2× 518 1.3× 176 0.6× 22 0.1× 143 1.9k
Özkan Çelik United States 12 343 0.3× 221 0.3× 159 0.4× 79 0.3× 99 0.6× 28 730
Mohamed Bouri Switzerland 22 713 0.7× 1.6k 1.9× 322 0.8× 58 0.2× 137 0.8× 105 2.3k
Shuai Cao China 19 110 0.1× 555 0.6× 339 0.9× 41 0.1× 123 0.7× 48 990
Mitsuhiro Hayashibe Japan 24 194 0.2× 1.1k 1.3× 599 1.6× 47 0.1× 78 0.4× 193 2.0k

Countries citing papers authored by Eric T. Wolbrecht

Since Specialization
Citations

This map shows the geographic impact of Eric T. Wolbrecht'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 T. Wolbrecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric T. Wolbrecht more than expected).

Fields of papers citing papers by Eric T. Wolbrecht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric T. Wolbrecht. 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 T. Wolbrecht. The network helps show where Eric T. Wolbrecht may publish in the future.

Co-authorship network of co-authors of Eric T. Wolbrecht

This figure shows the co-authorship network connecting the top 25 collaborators of Eric T. Wolbrecht. A scholar is included among the top collaborators of Eric T. Wolbrecht 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 T. Wolbrecht. Eric T. Wolbrecht 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
1.
2.
Perry, Joel C., et al.. (2024). Neural correlates of bilateral proprioception and adaptation with training. PLoS ONE. 19(3). e0299873–e0299873. 1 indexed citations
3.
4.
Weeks, Douglas L., et al.. (2023). Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability. Journal of NeuroEngineering and Rehabilitation. 20(1). 21–21. 45 indexed citations
5.
McFarland, Dennis J., Sumner L. Norman, William A. Sarnacki, et al.. (2020). BCI-based sensorimotor rhythm training can affect individuated finger movements. 7(1-2). 38–46. 7 indexed citations
6.
Ingemanson, Morgan L., et al.. (2019). Somatosensory system integrity explains differences in treatment response after stroke. Neurology. 92(10). e1098–e1108. 70 indexed citations
7.
Wolbrecht, Eric T., et al.. (2019). Scalability and Function of Lithium Thionyl Chloride Batteries for Encoders in High-Degree-of-Freedom Robotic Systems. Bulletin of the American Physical Society. 1 indexed citations
8.
Wolbrecht, Eric T., et al.. (2018). A task-based design methodology for robotic exoskeletons. SHILAP Revista de lepidopterología. 5. 2481654560–2481654560. 11 indexed citations
9.
Norman, Sumner L., Dennis J. McFarland, Steven C. Cramer, et al.. (2018). Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke. Journal of Neural Engineering. 15(5). 56026–56026. 36 indexed citations
10.
Wolbrecht, Eric T., Justin B. Rowe, Vicky Chan, et al.. (2018). Finger strength, individuation, and their interaction: Relationship to hand function and corticospinal tract injury after stroke. Clinical Neurophysiology. 129(4). 797–808. 42 indexed citations
11.
Rowe, Justin B., Vicky Chan, Morgan L. Ingemanson, et al.. (2017). Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial. Neurorehabilitation and neural repair. 31(8). 769–780. 72 indexed citations
12.
Ingemanson, Morgan L., Justin B. Rowe, Vicky Chan, et al.. (2015). Use of a robotic device to measure age-related decline in finger proprioception. Experimental Brain Research. 234(1). 83–93. 32 indexed citations
13.
Canning, John, et al.. (2013). Hybrid baseline localization for portable AUV navigation. 2013 OCEANS - San Diego. 1 indexed citations
14.
Anderson, Michael, et al.. (2013). Using AUV-acquired survey data to derive a magnetic model for a surface vessel. 2013 OCEANS - San Diego. 1–8. 2 indexed citations
15.
Rowe, James B., et al.. (2012). Robot-assisted Guitar Hero for finger rehabilitation after stroke. PubMed. 2012. 3911–3917. 20 indexed citations
16.
Reinkensmeyer, D.J., Marc A. Maier, Emmanuel Guigon, et al.. (2009). Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? experimental evidence and a computational model. PubMed. 2009. 2439–2441. 23 indexed citations
17.
Wolbrecht, Eric T., Vicky Chan, David J. Reinkensmeyer, & J.E. Bobrow. (2008). Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 16(3). 286–297. 365 indexed citations
18.
Reinkensmeyer, David J., Eric T. Wolbrecht, & J.E. Bobrow. (2007). A Computational Model of Human-Robot Load Sharing during Robot-Assisted Arm Movement Training after Stroke. Conference proceedings. 2007. 4019–4023. 34 indexed citations
19.
Reinkensmeyer, David J., José A. Gálvez, Laura Marchal–Crespo, Eric T. Wolbrecht, & J.E. Bobrow. (2007). Some Key Problems for Robot-Assisted Movement Therapy Research: A Perspective from the University of California at Irvine. 1009–1015. 28 indexed citations
20.
Wolbrecht, Eric T., J.A. Leavitt, David J. Reinkensmeyer, & J.E. Bobrow. (2006). Control of a Pneumatic Orthosis for Upper Extremity Stroke Rehabilitation. PubMed. 2006. 2687–2693. 48 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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