Paul E. Barkhaus

3.7k total citations
80 papers, 2.3k citations indexed

About

Paul E. Barkhaus is a scholar working on Neurology, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Paul E. Barkhaus has authored 80 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Neurology, 35 papers in Biomedical Engineering and 24 papers in Cellular and Molecular Neuroscience. Recurrent topics in Paul E. Barkhaus's work include Muscle activation and electromyography studies (35 papers), Amyotrophic Lateral Sclerosis Research (24 papers) and Neuroscience and Neural Engineering (19 papers). Paul E. Barkhaus is often cited by papers focused on Muscle activation and electromyography studies (35 papers), Amyotrophic Lateral Sclerosis Research (24 papers) and Neuroscience and Neural Engineering (19 papers). Paul E. Barkhaus collaborates with scholars based in United States, Sweden and United Kingdom. Paul E. Barkhaus's co-authors include Sanjeev D. Nandedkar, Erik Stålberg, Donald B. Sanders, Mamede de Carvalho, Ping Zhou, Christoph Neuwirth, Markus Weber, William Z. Rymer, Xu Zhang and James M. Gilchrist and has published in prestigious journals such as New England Journal of Medicine, Neurology and Journal of Neurology Neurosurgery & Psychiatry.

In The Last Decade

Paul E. Barkhaus

75 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul E. Barkhaus United States 25 978 827 617 577 432 80 2.3k
Masahiro Sonoo Japan 26 1.0k 1.1× 480 0.6× 593 1.0× 325 0.6× 236 0.5× 158 2.3k
P. Fawcett United Kingdom 23 825 0.8× 584 0.7× 538 0.9× 286 0.5× 592 1.4× 58 2.2k
Liying Cui China 30 2.0k 2.1× 292 0.4× 447 0.7× 723 1.3× 549 1.3× 226 3.5k
Wolfgang N. Löscher Austria 28 722 0.7× 408 0.5× 636 1.0× 177 0.3× 500 1.2× 125 2.8k
Kaan Yağmurlu United States 26 637 0.7× 353 0.4× 320 0.5× 298 0.5× 253 0.6× 117 2.1k
D A Ingram United Kingdom 26 640 0.7× 391 0.5× 442 0.7× 143 0.2× 466 1.1× 43 2.3k
Francis Mastaglia Australia 26 478 0.5× 391 0.5× 293 0.5× 139 0.2× 436 1.0× 79 2.3k
Christine K. Thomas United States 36 370 0.4× 1.7k 2.1× 892 1.4× 201 0.3× 415 1.0× 93 3.2k
Christian Krarup Denmark 35 1.2k 1.2× 661 0.8× 2.1k 3.4× 280 0.5× 572 1.3× 137 4.0k
Martin S. Schwartz United Kingdom 28 704 0.7× 281 0.3× 370 0.6× 216 0.4× 376 0.9× 83 2.0k

Countries citing papers authored by Paul E. Barkhaus

Since Specialization
Citations

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

Fields of papers citing papers by Paul E. Barkhaus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul E. Barkhaus. 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 Paul E. Barkhaus. The network helps show where Paul E. Barkhaus may publish in the future.

Co-authorship network of co-authors of Paul E. Barkhaus

This figure shows the co-authorship network connecting the top 25 collaborators of Paul E. Barkhaus. A scholar is included among the top collaborators of Paul E. Barkhaus 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 Paul E. Barkhaus. Paul E. Barkhaus 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.
Li, Xiaoyan, Maoqi Chen, Paul E. Barkhaus, et al.. (2024). F wave analysis based on the compound muscle action potential scan. Muscle & Nerve. 70(3). 395–401.
2.
Barkhaus, Paul E., Sanjeev D. Nandedkar, Mamede de Carvalho, Michael Swash, & Erik Stålberg. (2024). Revisiting the compound muscle action potential (CMAP). Clinical Neurophysiology Practice. 9. 176–200. 11 indexed citations
3.
Dumitru, Daniel, Sanjeev D. Nandedkar, & Paul E. Barkhaus. (2023). Volume conduction: Extracellular waveform generation in theory and practice. Muscle & Nerve. 67(6). 439–455. 3 indexed citations
4.
Pierce, Ellen S., Paul E. Barkhaus, Mark B. Bromberg, et al.. (2022). ALSUntangled #66: antimycobacterial antibiotics.. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration. 24(5-6). 539–543. 1 indexed citations
5.
Nandedkar, Sanjeev D., Paul E. Barkhaus, & Erik Stålberg. (2022). Motor unit recruitment and firing rate at low force of contraction. Muscle & Nerve. 66(6). 750–756. 7 indexed citations
6.
Nandedkar, Sanjeev D. & Paul E. Barkhaus. (2019). Influence of reference electrode position on the compound muscle action potential. Clinical Neurophysiology. 131(1). 160–166. 8 indexed citations
7.
Raghavan, Manoj, et al.. (2019). Generation and propagation of the action potential. Handbook of clinical neurology. 160. 3–22. 38 indexed citations
8.
Felgoise, Stephanie H., Richard A. Feinberg, Helen Stephens, et al.. (2018). ALS Specific Quality of Life- Short Form (ALSSQOL-SF): A Brief, Reliable and Valid Version of the ALSSQOL-R. Muscle & Nerve. 2 indexed citations
9.
Carvalho, Mamede de, Paul E. Barkhaus, Sanjeev D. Nandedkar, & Michael Swash. (2018). Motor unit number estimation (MUNE): Where are we now?. Clinical Neurophysiology. 129(8). 1507–1516. 72 indexed citations
10.
Barkhaus, Paul E., et al.. (2015). Innervation zones of fasciculating motor units: observations by a linear electrode array. Frontiers in Human Neuroscience. 9. 239–239. 13 indexed citations
11.
Barkhaus, Paul E., et al.. (2014). Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials. Computers in Biology and Medicine. 55. 26–35. 6 indexed citations
12.
Barkhaus, Paul E., John C. Kincaid, & Sanjeev D. Nandedkar. (2011). Tibial motor nerve conduction studies: An investigation into the mechanism for amplitude drop of the proximal evoked response. Muscle & Nerve. 44(5). 776–782. 22 indexed citations
13.
Neuwirth, Christoph, Sanjeev D. Nandedkar, Erik Stålberg, et al.. (2011). Motor Unit Number Index (MUNIX): A novel neurophysiological marker for neuromuscular disorders; test–retest reliability in healthy volunteers. Clinical Neurophysiology. 122(9). 1867–1872. 93 indexed citations
14.
Zhou, Ping, Paul E. Barkhaus, Xu Zhang, & William Z. Rymer. (2011). Characterizing the complexity of spontaneous motor unit patterns of amyotrophic lateral sclerosis using approximate entropy. Journal of Neural Engineering. 8(6). 66010–66010. 28 indexed citations
15.
Barkhaus, Paul E., et al.. (2009). Cranial Nerve XII: The Hypoglossal Nerve. Seminars in Neurology. 29(1). 45–52. 24 indexed citations
16.
Barkhaus, Paul E., et al.. (1999). Quantitative electrophysiologic studies in sporadic inclusion body myositis. Muscle & Nerve. 22(4). 480–487. 33 indexed citations
17.
Barkhaus, Paul E., et al.. (1997). Quantitative motor unit action potential analysis in paraspinal muscles. Muscle & Nerve. 20(3). 373–375. 20 indexed citations
18.
Barkhaus, Paul E. & Sanjeev D. Nandedkar. (1994). Recording characteristics of the surface EMG electrodes. Muscle & Nerve. 17(11). 1317–1323. 54 indexed citations
19.
Barkhaus, Paul E. & Owen Morgan. (1988). Jamaican neuropathy: An electrophysiological study. Muscle & Nerve. 11(4). 380–385. 11 indexed citations
20.
Gilchrist, James M., et al.. (1988). Automatic analysis of the electromyographic interference pattern using the turns: amplitude ratio. Electroencephalography and Clinical Neurophysiology. 70(6). 534–540. 20 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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