Marko Marković

1.6k total citations
34 papers, 1.1k citations indexed

About

Marko Marković is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Marko Marković has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Biomedical Engineering, 23 papers in Cognitive Neuroscience and 16 papers in Cellular and Molecular Neuroscience. Recurrent topics in Marko Marković's work include Muscle activation and electromyography studies (23 papers), Neuroscience and Neural Engineering (16 papers) and EEG and Brain-Computer Interfaces (12 papers). Marko Marković is often cited by papers focused on Muscle activation and electromyography studies (23 papers), Neuroscience and Neural Engineering (16 papers) and EEG and Brain-Computer Interfaces (12 papers). Marko Marković collaborates with scholars based in Germany, Serbia and Denmark. Marko Marković's co-authors include Dario Farina, Strahinja Došen, Bernhard Graimann, Dejan B. Popović, Meike A. Schweisfurth, Matija Štrbac, Janne M. Hahne, Christian Cipriani, Leonard F. Engels and Goran Bijelić and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Experimental Brain Research.

In The Last Decade

Marko Marković

33 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marko Marković Germany 18 945 784 538 91 82 34 1.1k
Francesco Clemente Italy 20 1.1k 1.2× 835 1.1× 646 1.2× 89 1.0× 105 1.3× 47 1.4k
Anna Lisa Ciancio Italy 12 759 0.8× 470 0.6× 386 0.7× 43 0.5× 115 1.4× 22 918
Rahul R. Kaliki United States 14 758 0.8× 583 0.7× 430 0.8× 93 1.0× 40 0.5× 32 905
Jiayuan He China 16 759 0.8× 471 0.6× 313 0.6× 206 2.3× 54 0.7× 54 945
Sanford G. Meek United States 18 934 1.0× 630 0.8× 341 0.6× 60 0.7× 226 2.8× 40 1.2k
Evelyn Morin Canada 14 842 0.9× 558 0.7× 243 0.5× 70 0.8× 37 0.5× 52 1.0k
Luke E. Osborn United States 16 655 0.7× 593 0.8× 450 0.8× 72 0.8× 26 0.3× 46 950
Christian Antfolk Sweden 22 1.6k 1.7× 1.2k 1.6× 710 1.3× 188 2.1× 72 0.9× 62 1.8k
Ivan Vujaklija Finland 24 1.8k 1.9× 1.1k 1.4× 1.0k 1.9× 125 1.4× 52 0.6× 53 2.0k
Jacob L. Segil United States 12 794 0.8× 398 0.5× 375 0.7× 41 0.5× 231 2.8× 24 899

Countries citing papers authored by Marko Marković

Since Specialization
Citations

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

Fields of papers citing papers by Marko Marković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marko Marković

This figure shows the co-authorship network connecting the top 25 collaborators of Marko Marković. A scholar is included among the top collaborators of Marko Marković 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 Marko Marković. Marko Marković 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.
Dideriksen, Jakob Lund, et al.. (2024). Investigating the Benefits of Multivariable Proprioceptive Feedback for Upper-Limb Prostheses. IEEE Transactions on Medical Robotics and Bionics. 6(2). 757–768. 3 indexed citations
2.
3.
Marković, Marko, et al.. (2022). Vibrotactile mapping of the upper extremity: Absolute perceived intensity is location-dependent; perception of relative changes is not. Frontiers in Neuroscience. 16. 958415–958415. 5 indexed citations
4.
Došen, Strahinja, et al.. (2021). Artificial Perception and Semiautonomous Control in Myoelectric Hand Prostheses Increases Performance and Decreases Effort. IEEE Transactions on Robotics. 37(4). 1298–1312. 33 indexed citations
5.
Hahne, Janne M., et al.. (2021). On the Utility of Bioimpedance in the Context of Myoelectric Control. IEEE Sensors Journal. 21(17). 19505–19515. 4 indexed citations
6.
Dideriksen, Jakob Lund, et al.. (2021). Electrotactile and Vibrotactile Feedback Enable Similar Performance in Psychometric Tests and Closed-Loop Control. IEEE Transactions on Haptics. 15(1). 222–231. 8 indexed citations
7.
Marković, Marko, et al.. (2021). The effect of calibration parameters on the control of a myoelectric hand prosthesis using EMG feedback. Journal of Neural Engineering. 18(4). 46091–46091. 19 indexed citations
8.
Došen, Strahinja, et al.. (2021). Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses. Frontiers in Neurorobotics. 15. 768619–768619. 5 indexed citations
9.
Marković, Marko, et al.. (2019). Closed-Loop Multi-Amplitude Control for Robust and Dexterous Performance of Myoelectric Prosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 28(2). 498–507. 15 indexed citations
10.
Došen, Strahinja, et al.. (2019). Improving bimanual interaction with a prosthesis using semi-autonomous control. Journal of NeuroEngineering and Rehabilitation. 16(1). 140–140. 22 indexed citations
11.
Marković, Marko, et al.. (2018). The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis. Journal of NeuroEngineering and Rehabilitation. 15(1). 28–28. 93 indexed citations
12.
Marković, Marko, Meike A. Schweisfurth, Leonard F. Engels, Dario Farina, & Strahinja Došen. (2018). Myocontrol is closed-loop control: incidental feedback is sufficient for scaling the prosthesis force in routine grasping. Journal of NeuroEngineering and Rehabilitation. 15(1). 81–81. 49 indexed citations
13.
Hahne, Janne M., Marko Marković, & Dario Farina. (2017). User adaptation in Myoelectric Man-Machine Interfaces. Scientific Reports. 7(1). 4437–4437. 93 indexed citations
14.
Nunzio, Alessandro Marco De, Strahinja Došen, Marko Marković, et al.. (2017). Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels. Experimental Brain Research. 235(8). 2547–2559. 48 indexed citations
15.
Marković, Marko, et al.. (2017). GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses. Journal of Neural Engineering. 14(3). 36007–36007. 41 indexed citations
16.
Štrbac, Matija, Minja Belić, Milica Isaković, et al.. (2016). Integrated and flexible multichannel interface for electrotactile stimulation. Journal of Neural Engineering. 13(4). 46014–46014. 81 indexed citations
17.
Schweisfurth, Meike A., et al.. (2016). Electrotactile EMG feedback improves the control of prosthesis grasping force. Journal of Neural Engineering. 13(5). 56010–56010. 77 indexed citations
18.
Došen, Strahinja, et al.. (2015). EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis. Journal of NeuroEngineering and Rehabilitation. 12(1). 55–55. 72 indexed citations
19.
Došen, Strahinja, et al.. (2015). Building an internal model of a myoelectric prosthesis via closed-loop control for consistent and routine grasping. Experimental Brain Research. 233(6). 1855–1865. 35 indexed citations
20.
Marković, Marko, et al.. (2014). INSOS—educational system for teaching intelligent systems. Computer Applications in Engineering Education. 23(2). 268–276. 4 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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