Michelle J. Johnson

2.5k total citations
117 papers, 1.6k citations indexed

About

Michelle J. Johnson is a scholar working on Rehabilitation, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Michelle J. Johnson has authored 117 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Rehabilitation, 25 papers in Biomedical Engineering and 24 papers in Cognitive Neuroscience. Recurrent topics in Michelle J. Johnson's work include Stroke Rehabilitation and Recovery (74 papers), Cerebral Palsy and Movement Disorders (24 papers) and Botulinum Toxin and Related Neurological Disorders (22 papers). Michelle J. Johnson is often cited by papers focused on Stroke Rehabilitation and Recovery (74 papers), Cerebral Palsy and Movement Disorders (24 papers) and Botulinum Toxin and Related Neurological Disorders (22 papers). Michelle J. Johnson collaborates with scholars based in United States, Germany and United Kingdom. Michelle J. Johnson's co-authors include William Harwin, Rui Loureiro, Kiyoshi Nagai, Dominic E. Nathan, Jack M. Winters, Laura Johnson, John R. McGuire, Leah R. Enders, Na Jin Seo and Xin Feng and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nutrients and Archives of Physical Medicine and Rehabilitation.

In The Last Decade

Michelle J. Johnson

108 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
Michelle J. Johnson United States 21 885 503 390 280 262 117 1.6k
Farshid Amirabdollahian United Kingdom 20 1.0k 1.2× 722 1.4× 738 1.9× 335 1.2× 220 0.8× 77 2.3k
Ann‐Marie Hughes United Kingdom 27 1.2k 1.4× 917 1.8× 464 1.2× 297 1.1× 275 1.0× 103 2.2k
Rosalie H. Wang Canada 19 430 0.5× 231 0.5× 161 0.4× 102 0.4× 228 0.9× 62 1.2k
Mónica S. Cameirão Portugal 18 927 1.0× 160 0.3× 314 0.8× 263 0.9× 273 1.0× 52 1.4k
Bruno Bonnechère Belgium 20 438 0.5× 181 0.4× 122 0.3× 172 0.6× 391 1.5× 129 1.5k
David Putrino United States 23 316 0.4× 199 0.4× 372 1.0× 339 1.2× 202 0.8× 100 1.6k
Lucy Dodakian United States 17 832 0.9× 144 0.3× 405 1.0× 236 0.8× 219 0.8× 30 1.3k
Bambi R. Brewer United States 13 388 0.4× 250 0.5× 193 0.5× 176 0.6× 117 0.4× 24 669
Gill Barry United Kingdom 16 316 0.4× 338 0.7× 99 0.3× 221 0.8× 338 1.3× 56 1.5k
Kynan Eng Switzerland 19 372 0.4× 131 0.3× 335 0.9× 82 0.3× 186 0.7× 47 1.0k

Countries citing papers authored by Michelle J. Johnson

Since Specialization
Citations

This map shows the geographic impact of Michelle J. Johnson'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 Michelle J. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelle J. Johnson more than expected).

Fields of papers citing papers by Michelle J. Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle J. Johnson. 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 Michelle J. Johnson. The network helps show where Michelle J. Johnson may publish in the future.

Co-authorship network of co-authors of Michelle J. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle J. Johnson. A scholar is included among the top collaborators of Michelle J. Johnson 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 Michelle J. Johnson. Michelle J. Johnson 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.
Johnson, Michelle J., et al.. (2024). Motor Learning in Robot-Based Haptic Dyads: A Review. IEEE Transactions on Haptics. 17(4). 510–527. 2 indexed citations
3.
Yin, Jessica, et al.. (2024). Towards an AI-driven soft toy for automatically detecting and classifying infant-toy interactions using optical force sensors. Frontiers in Robotics and AI. 11. 1325296–1325296. 1 indexed citations
4.
Cacchione, Pamela Z., et al.. (2024). TheraDyad: Feasibility of an Affordable Robot for Multi-User Stroke Rehabilitation. PubMed. 2024. 1498–1503. 1 indexed citations
5.
Johnson, Michelle J., et al.. (2023). Design of an Affordable Socially Assistive Robot for Remote Health and Function Monitoring and Prognostication. International Journal of Prognostics and Health Management. 10(3). 3 indexed citations
6.
Toonkel, Rebecca L., Analia Castiglioni, Jennifer Foster, et al.. (2022). The Florida Clinical Skills Collaborative: A New Regional Consortium for the Assessment of Clinical Skills. Cureus. 14(11). e31263–e31263.
7.
Johnson, Michelle J., et al.. (2021). The design of Lil’Flo, a socially assistive robot for upper extremity motor assessment and rehabilitation in the community via telepresence. Journal of Rehabilitation and Assistive Technologies Engineering. 8. 3364704205–3364704205. 6 indexed citations
8.
Aarts, Pauline, Susanna Freivogel, Michelle J. Johnson, et al.. (2021). A First Step Toward the Operationalization of the Learned Non-Use Phenomenon: A Delphi Study. Neurorehabilitation and neural repair. 35(5). 383–392. 14 indexed citations
9.
Carpino, Giorgio, et al.. (2021). Affordable Robotics for Upper Limb Stroke Rehabilitation in Developing Countries: A Systematic Review. IEEE Transactions on Medical Robotics and Bionics. 3(1). 11–20. 38 indexed citations
10.
Seethapathi, Nidhi, et al.. (2020). Towards Automated Emotion Classification of Atypically and Typically Developing Infants. PubMed. 2020. 503–508. 2 indexed citations
11.
Johnson, Michelle J., et al.. (2018). Designing robot-assisted neurorehabilitation strategies for people with both HIV and stroke. Journal of NeuroEngineering and Rehabilitation. 15(1). 5 indexed citations
12.
Pathak, Yagna & Michelle J. Johnson. (2012). An upper limb robot model of children limb for cerebral palsy neurorehabilitation. PubMed. 128. 1936–1939. 2 indexed citations
13.
Johnson, Michelle J., et al.. (2011). Quantifying learned non-use after stroke using unilateral and bilateral steering tasks. PubMed. 2011. 1–7. 10 indexed citations
14.
Loureiro, Rui, William Harwin, Kiyoshi Nagai, & Michelle J. Johnson. (2011). Advances in upper limb stroke rehabilitation: a technology push. Medical & Biological Engineering & Computing. 49(10). 1103–1118. 165 indexed citations
15.
Nathan, Dominic E., Michelle J. Johnson, & John R. McGuire. (2009). Design and validation of low-cost assistive glove for hand assessment and therapy during activity of daily living-focused robotic stroke therapy. The Journal of Rehabilitation Research and Development. 46(5). 587–587. 37 indexed citations
16.
Ruparel, Raaj K., et al.. (2009). Evaluation of the TheraDrive system for robot/computer assisted motivating rehabilitation after stroke. PubMed. 192. 811–814. 10 indexed citations
17.
18.
Johnson, Michelle J., et al.. (2007). Quantifying kinematics of purposeful movements to real, imagined, or absent functional objects: Implications for modelling trajectories for robot-assisted ADL tasks**. Journal of NeuroEngineering and Rehabilitation. 4(1). 7–7. 50 indexed citations
19.
Schneider, Johannes, et al.. (2006). Combined sagittal and coronal plane postural stability model. PubMed. 2006. 4576–4579. 12 indexed citations
20.
Johnson, Michelle J., et al.. (2005). TheraDrive: a new stroke therapy concept for home-based, computer-assisted motivating rehabilitation. PubMed. 4. 4844–4847. 33 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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