Nicholas Kirsch

569 total citations
22 papers, 459 citations indexed

About

Nicholas Kirsch is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience and Pathology and Forensic Medicine. According to data from OpenAlex, Nicholas Kirsch has authored 22 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Biomedical Engineering, 12 papers in Cellular and Molecular Neuroscience and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Nicholas Kirsch's work include Muscle activation and electromyography studies (21 papers), Prosthetics and Rehabilitation Robotics (15 papers) and Neuroscience and Neural Engineering (12 papers). Nicholas Kirsch is often cited by papers focused on Muscle activation and electromyography studies (21 papers), Prosthetics and Rehabilitation Robotics (15 papers) and Neuroscience and Neural Engineering (12 papers). Nicholas Kirsch collaborates with scholars based in United States. Nicholas Kirsch's co-authors include Nitin Sharma, Naji Alibeji, Brad E. Dicianno, Xuefeng Bao, Shawn Farrokhi, Warren E. Dixon, Lee E. Fisher, Chris M. Gregory, Ashwin P. Dani and William W. Clark and has published in prestigious journals such as Muscle & Nerve, IEEE/ASME Transactions on Mechatronics and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

In The Last Decade

Nicholas Kirsch

21 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicholas Kirsch United States 12 417 149 118 92 82 22 459
Naji Alibeji United States 12 441 1.1× 169 1.1× 119 1.0× 98 1.1× 100 1.2× 21 499
Cheryl L. Lynch Canada 8 323 0.8× 130 0.9× 137 1.2× 154 1.7× 59 0.7× 11 424
R. Davoodi United States 9 323 0.8× 118 0.8× 95 0.8× 160 1.7× 99 1.2× 18 395
Joris M. Lambrecht United States 9 344 0.8× 84 0.6× 175 1.5× 226 2.5× 40 0.5× 16 449
Matthew J. Bellman United States 13 424 1.0× 134 0.9× 186 1.6× 122 1.3× 46 0.6× 16 461
Victor H. Duenas United States 11 267 0.6× 128 0.9× 108 0.9× 82 0.9× 24 0.3× 42 336
H.J. Chizeck United States 9 466 1.1× 76 0.5× 215 1.8× 224 2.4× 67 0.8× 19 535
Giovanni Cannaviello Italy 7 253 0.6× 247 1.7× 49 0.4× 87 0.9× 39 0.5× 10 420
Xuefeng Bao United States 11 242 0.6× 115 0.8× 33 0.3× 29 0.3× 55 0.7× 28 322
D. S. V. Bandara Japan 9 493 1.2× 285 1.9× 62 0.5× 104 1.1× 20 0.2× 24 587

Countries citing papers authored by Nicholas Kirsch

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Kirsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicholas Kirsch. 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 Nicholas Kirsch. The network helps show where Nicholas Kirsch may publish in the future.

Co-authorship network of co-authors of Nicholas Kirsch

This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Kirsch. A scholar is included among the top collaborators of Nicholas Kirsch 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 Nicholas Kirsch. Nicholas Kirsch 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.
Bao, Xuefeng, et al.. (2019). Model Predictive Control of a Feedback-Linearized Hybrid Neuroprosthetic System With a Barrier Penalty. Journal of Computational and Nonlinear Dynamics. 14(10). 101009–1010097. 14 indexed citations
2.
Alibeji, Naji, Nicholas Kirsch, Brad E. Dicianno, & Nitin Sharma. (2017). A Modified Dynamic Surface Controller for Delayed Neuromuscular Electrical Stimulation. IEEE/ASME Transactions on Mechatronics. 22(4). 1755–1764. 17 indexed citations
3.
Sharma, Nitin, Nicholas Kirsch, Naji Alibeji, & Warren E. Dixon. (2017). A Non-Linear Control Method to Compensate for Muscle Fatigue during Neuromuscular Electrical Stimulation. Frontiers in Robotics and AI. 4. 26 indexed citations
4.
Kirsch, Nicholas, Xuefeng Bao, Naji Alibeji, Brad E. Dicianno, & Nitin Sharma. (2017). Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(1). 224–232. 66 indexed citations
5.
Kirsch, Nicholas, et al.. (2017). A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25(12). 2365–2374. 7 indexed citations
6.
Kirsch, Nicholas, et al.. (2017). Dynamic optimization of stimulation frequency to reduce isometric muscle fatigue using a modified Hill‐Huxley model. Muscle & Nerve. 57(4). 634–641. 22 indexed citations
7.
Bao, Xuefeng, Nicholas Kirsch, & Nitin Sharma. (2016). Dynamic control allocation of a feedback linearized hybrid neuroprosthetic system. 3976–3981. 11 indexed citations
8.
Kirsch, Nicholas, Naji Alibeji, & Nitin Sharma. (2016). Nonlinear model predictive control of functional electrical stimulation. Control Engineering Practice. 58. 319–331. 83 indexed citations
9.
Alibeji, Naji, Nicholas Kirsch, & Nitin Sharma. (2016). An adaptive low-dimensional control to compensate for actuator redundancy and FES-induced muscle fatigue in a hybrid neuroprosthesis. Control Engineering Practice. 59. 204–219. 44 indexed citations
10.
Kirsch, Nicholas. (2016). Control methods for compensation and inhibition of muscle fatigue in neuroprosthetic devices. D-Scholarship@Pitt (University of Pittsburgh). 4 indexed citations
11.
Alibeji, Naji, Nicholas Kirsch, & Nitin Sharma. (2015). A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis. Frontiers in Bioengineering and Biotechnology. 3. 203–203. 39 indexed citations
12.
Kirsch, Nicholas, et al.. (2015). Optimization of a Stimulation Train based on a Predictive Model of Muscle Force and Fatigue. IFAC-PapersOnLine. 48(20). 338–342. 8 indexed citations
13.
14.
Alibeji, Naji, Nicholas Kirsch, Shawn Farrokhi, & Nitin Sharma. (2015). Further Results on Predictor-Based Control of Neuromuscular Electrical Stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 23(6). 1095–1105. 39 indexed citations
15.
Alibeji, Naji, Nicholas Kirsch, & Nitin Sharma. (2015). An Adaptive Low-Dimensional Control for a Hybrid Neuroprosthesis. IFAC-PapersOnLine. 48(20). 303–308. 3 indexed citations
16.
Kirsch, Nicholas, Naji Alibeji, Lee E. Fisher, Chris M. Gregory, & Nitin Sharma. (2014). A semi-active hybrid neuroprosthesis for restoring lower limb function in paraplegics. PubMed. 2014. 2557–60. 20 indexed citations
17.
Kirsch, Nicholas, Naji Alibeji, & Nitin Sharma. (2014). Model Predictive Control-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis. 11 indexed citations
18.
Kirsch, Nicholas, Naji Alibeji, & Nitin Sharma. (2013). Optimized Control of Different Actuation Strategies for FES and Orthosis Aided Gait. 8 indexed citations
19.
Alibeji, Naji, Nicholas Kirsch, & Nitin Sharma. (2013). Control of functional electrical stimulation in the presence of electromechanical and communication delays. 6. 299–302. 5 indexed citations
20.
Kirsch, Nicholas. (2012). Characterization of Periodic Disturbances In Rolling Element Bearings. D-Scholarship@Pitt (University of Pittsburgh).

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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2026