G.F. Inbar

2.9k total citations
82 papers, 2.1k citations indexed

About

G.F. Inbar is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, G.F. Inbar has authored 82 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Biomedical Engineering, 43 papers in Cognitive Neuroscience and 11 papers in Cellular and Molecular Neuroscience. Recurrent topics in G.F. Inbar's work include Muscle activation and electromyography studies (40 papers), Motor Control and Adaptation (23 papers) and EEG and Brain-Computer Interfaces (23 papers). G.F. Inbar is often cited by papers focused on Muscle activation and electromyography studies (40 papers), Motor Control and Adaptation (23 papers) and EEG and Brain-Computer Interfaces (23 papers). G.F. Inbar collaborates with scholars based in Israel, United States and Germany. G.F. Inbar's co-authors include Elad Yom‐Tov, Amir Karniel, H Kranz, Hillel Pratt, Dori Peleg, Paul Milgram, Gad Alon, Irving H. Wagman, Uwe Windhorst and P. Rudomín and has published in prestigious journals such as IEEE Transactions on Automatic Control, Journal of Applied Physiology and IEEE Transactions on Biomedical Engineering.

In The Last Decade

G.F. Inbar

76 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G.F. Inbar Israel 28 1.3k 899 506 192 159 82 2.1k
Stan Gielen Netherlands 27 1.6k 1.2× 365 0.4× 404 0.8× 158 0.8× 117 0.7× 64 3.0k
Po‐Lei Lee Taiwan 27 1.3k 1.0× 401 0.4× 516 1.0× 254 1.3× 160 1.0× 97 2.2k
Francisco Sepulveda United Kingdom 20 1.2k 1.0× 427 0.5× 567 1.1× 253 1.3× 253 1.6× 88 1.7k
Yasuharu Koike Japan 30 2.1k 1.6× 1.1k 1.2× 557 1.1× 242 1.3× 420 2.6× 203 2.9k
Sylvie Charbonnier France 17 833 0.6× 702 0.8× 252 0.5× 100 0.5× 249 1.6× 35 1.5k
Yasue Mitsukura Japan 18 1.0k 0.8× 273 0.3× 366 0.7× 256 1.3× 250 1.6× 251 1.9k
Bo Hjorth Sweden 10 1.9k 1.4× 296 0.3× 375 0.7× 346 1.8× 128 0.8× 12 2.3k
Adrian D. C. Chan Canada 26 701 0.5× 1.2k 1.4× 300 0.6× 166 0.9× 202 1.3× 135 2.3k
Muhammad Jawad Khan Pakistan 22 1.4k 1.1× 800 0.9× 412 0.8× 97 0.5× 223 1.4× 85 2.0k
Noman Naseer Pakistan 24 2.0k 1.6× 1.5k 1.7× 479 0.9× 144 0.8× 220 1.4× 105 3.1k

Countries citing papers authored by G.F. Inbar

Since Specialization
Citations

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

Fields of papers citing papers by G.F. Inbar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G.F. Inbar. 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 G.F. Inbar. The network helps show where G.F. Inbar may publish in the future.

Co-authorship network of co-authors of G.F. Inbar

This figure shows the co-authorship network connecting the top 25 collaborators of G.F. Inbar. A scholar is included among the top collaborators of G.F. Inbar 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 G.F. Inbar. G.F. Inbar 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.
Yom‐Tov, Elad, et al.. (2005). An improved P300-based brain-computer interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 13(1). 89–98. 318 indexed citations
2.
Inbar, G.F., Yossef Steinberg, Miloš Ljubisavljević, et al.. (2005). Estimation of muscle spindle information rate by pattern matching and the effect of gamma system activity on parallel spindles. Biological Cybernetics. 92(5). 316–332. 6 indexed citations
3.
Inbar, G.F., et al.. (2005). On the effects of adaptation to changing loads on movement-related EEG potentials. Biological Cybernetics. 93(3). 171–177. 5 indexed citations
4.
Rubin, Daniel Ben Dayan, Giuseppe Baselli, G.F. Inbar, & S. Cerutti. (2004). An adaptive neuro-fuzzy method (ANFIS) for estimating single-trial movement-related potentials. Biological Cybernetics. 91(2). 63–75. 8 indexed citations
5.
Steinberg, Yossef, G.F. Inbar, Miloš Ljubisavljević, et al.. (2003). Estimation of muscle spindle information rate by pattern matching and effects of the fusimotor system. 51–54. 2 indexed citations
6.
Yom‐Tov, Elad & G.F. Inbar. (2003). Detection of movement-related potentials from the electro-encephalogram for possible use in a brain-computer interface. Medical & Biological Engineering & Computing. 41(1). 85–93. 45 indexed citations
7.
Peleg, Dori, et al.. (2002). Classification of finger activation for use in a robotic prosthesis arm. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 10(4). 290–293. 102 indexed citations
8.
Yom‐Tov, Elad & G.F. Inbar. (2002). Feature selection for the classification of movements from single movement-related potentials. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 10(3). 170–177. 78 indexed citations
9.
Yom‐Tov, Elad, Aaron W. Grossman, & G.F. Inbar. (2001). Movement-related potentials during the performance of a motor task I: The effect of learning and force. Biological Cybernetics. 85(5). 395–399. 6 indexed citations
10.
Yom‐Tov, Elad & G.F. Inbar. (2000). Movement-related potentials in the human spinal cord preceding toe movement. Clinical Neurophysiology. 111(2). 350–361. 3 indexed citations
11.
Siegelmann, Hava T., et al.. (2000). Overcoming selective ensemble averaging: unsupervised identification of event-related brain potentials. IEEE Transactions on Biomedical Engineering. 47(6). 822–826. 18 indexed citations
12.
Karniel, Amir & G.F. Inbar. (1999). The Use of a Nonlinear Muscle Model in Explaining the Relationship Between Duration, Amplitude, and Peak Velocity of Human Rapid Movements. Journal of Motor Behavior. 31(3). 203–206. 10 indexed citations
13.
Karniel, Amir, Ron Meir, & G.F. Inbar. (1998). Polyhedral Mixture of Linear Experts for Many-To-One Mapping Inversion. The European Symposium on Artificial Neural Networks. 155–160. 4 indexed citations
14.
Siegelmann, Hava T., et al.. (1997). A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure. Neural Information Processing Systems. 10. 901–907. 1 indexed citations
15.
Pratt, Hillel, et al.. (1997). Modeling and estimation of single evoked brain potential components. IEEE Transactions on Biomedical Engineering. 44(9). 791–799. 60 indexed citations
16.
Inbar, G.F., et al.. (1996). A robust parametric estimator for single-trial movement related brain potentials. IEEE Transactions on Biomedical Engineering. 43(4). 341–347. 22 indexed citations
17.
Leviatan, Y., et al.. (1992). Simulation method for cardiac stroke volume estimation by intracardiac electrical impedance measurement. Medical & Biological Engineering & Computing. 30(5). 473–480. 2 indexed citations
18.
Inbar, G.F., et al.. (1988). Autoregressive modeling of surface EMG and its spectrum with application to fatigue. Mathematical and Computer Modelling. 10(10). 793–794. 2 indexed citations
19.
Inbar, G.F., et al.. (1979). The influence of the gamma system on cross-correlated activity of Ia muscle spindles and its relation to information transmission. Neuroscience Letters. 13(1). 73–78. 48 indexed citations
20.
Inbar, G.F., et al.. (1976). Parameter and Signal Adaptation in the Stretch Reflex Loop. Progress in brain research. 44. 317–337. 61 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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