Matthew A. Schiefer

2.8k citations
37 papers · 2.0k indexed · 1 hit paper · h-index 18
Topics
Neuroscience and Neural Engineering (26 papers)Muscle activation and electromyography studies (22 papers)EEG and Brain-Computer Interfaces (12 papers)

In The Last Decade

Matthew A. Schiefer

35 papers receiving 2.0k citations

Hit Papers

A neural interface provides long-term stable natural touc...20142026201820222014100200300400500

Peers

Matthew A. Schiefer
Comparison fields: 5 of 89
  • Cellular and Molecular Neuroscience 1.4k
  • Biomedical Engineering 1.4k
  • Cognitive Neuroscience 1.2k
  • Neurology 256
  • Electrical and Electronic Engineering 92
Replace Robert A. Gaunt with:
Robert A. Gaunt United States
Giacomo Valle Switzerland
Jacopo Carpaneto Italy
Francesco M. Petrini Switzerland
Winnie Jensen Denmark
Niloy Bhadra United States
Silvia Muceli United Kingdom
Marco Capogrosso Switzerland
Daniel Tan United States
Christian Éthier Canada
Matthew A. Schiefer relative to Robert A. Gaunt United States Robert A. Gaunt's profile →
Citations per field
00.5×1.5×
Robert A. Gaunt · 1×
Citations per year

Countries citing papers authored by Matthew A. Schiefer

Since Specialization
Citations

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

Fields of papers citing papers by Matthew A. Schiefer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew A. Schiefer. 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 Matthew A. Schiefer. The network helps show where Matthew A. Schiefer may publish in the future.

Co-authorship network of co-authors of Matthew A. Schiefer

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew A. Schiefer. A scholar is included among the top collaborators of Matthew A. Schiefer 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 Matthew A. Schiefer. Matthew A. Schiefer 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
#WorkIndexed citations
1 1
2 0
3 23
4 15
5 23
6 3
7 86
8 8
9 150
10 81
11 134
12 48
13 29
14 2
15 97
16 24
17 9
18 0
19 57
20 4

About Matthew A. Schiefer

Matthew A. Schiefer is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Neurology, having authored 37 papers that have together received 2.0k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (26 papers), Muscle activation and electromyography studies (22 papers) and EEG and Brain-Computer Interfaces (12 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.4k citations), Cognitive Neuroscience (1.2k citations) and Neurology (256 citations). Matthew A. Schiefer has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Dustin J. Tyler, Daniel Tan, Michael W. Keith, Emily L. Graczyk, Ronald J. Triolo, Benoit P. Delhaye, Sliman J. Bensmaı̈a, Hannes P. Saal, Linda Resnik and Kenneth J. Gustafson. Their work appears in journals such as PLoS ONE, Scientific Reports and Brain Research.

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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