Erik D. Engeberg

1.5k total citations
77 papers, 1.2k citations indexed

About

Erik D. Engeberg is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Control and Systems Engineering. According to data from OpenAlex, Erik D. Engeberg has authored 77 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Biomedical Engineering, 55 papers in Cognitive Neuroscience and 23 papers in Control and Systems Engineering. Recurrent topics in Erik D. Engeberg's work include Muscle activation and electromyography studies (50 papers), EEG and Brain-Computer Interfaces (26 papers) and Motor Control and Adaptation (22 papers). Erik D. Engeberg is often cited by papers focused on Muscle activation and electromyography studies (50 papers), EEG and Brain-Computer Interfaces (26 papers) and Motor Control and Adaptation (22 papers). Erik D. Engeberg collaborates with scholars based in United States, Türkiye and Spain. Erik D. Engeberg's co-authors include Sanford G. Meek, Morteza Vatani, Jae‐Won Choi, Savaş Dilibal, Oscar Curet, Maohua Lin, John E. Lavery, Mark A. Minor, Yanfeng Lu and Frank D. Vrionis and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Erik D. Engeberg

72 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erik D. Engeberg United States 19 954 511 300 220 174 77 1.2k
Rahim Mutlu Australia 22 1.3k 1.4× 256 0.5× 477 1.6× 130 0.6× 356 2.0× 55 1.5k
Andrew McDaid New Zealand 23 1.1k 1.2× 140 0.3× 193 0.6× 82 0.4× 178 1.0× 109 1.4k
Ningbin Zhang China 16 1.4k 1.5× 246 0.5× 367 1.2× 83 0.4× 532 3.1× 30 1.8k
Haipeng Xu China 15 676 0.7× 237 0.5× 126 0.4× 84 0.4× 195 1.1× 24 865
Benjamin Shih United States 13 1.4k 1.5× 380 0.7× 293 1.0× 31 0.1× 476 2.7× 18 1.7k
Mohsen Kaboli Germany 17 719 0.8× 657 1.3× 306 1.0× 89 0.4× 116 0.7× 43 1.4k
Perla Maiolino United Kingdom 18 996 1.0× 583 1.1× 405 1.4× 45 0.2× 337 1.9× 79 1.4k
Tess Hellebrekers United States 12 863 0.9× 234 0.5× 121 0.4× 27 0.1× 286 1.6× 18 1.0k
Zhiwei Luo Japan 23 1.3k 1.4× 271 0.5× 527 1.8× 31 0.1× 322 1.9× 145 1.8k
Lisen Ge China 9 803 0.8× 127 0.2× 248 0.8× 54 0.2× 284 1.6× 10 878

Countries citing papers authored by Erik D. Engeberg

Since Specialization
Citations

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

Fields of papers citing papers by Erik D. Engeberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik D. Engeberg. 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 Erik D. Engeberg. The network helps show where Erik D. Engeberg may publish in the future.

Co-authorship network of co-authors of Erik D. Engeberg

This figure shows the co-authorship network connecting the top 25 collaborators of Erik D. Engeberg. A scholar is included among the top collaborators of Erik D. Engeberg 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 Erik D. Engeberg. Erik D. Engeberg 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.
Ahmadi, Mohsen, Hanxi Chen, Maohua Lin, et al.. (2025). Streamlined and efficient patient-specific modeling for lumbar spine segmentation and finite element analysis. Scientific Reports. 15(1). 35619–35619.
2.
Ahmadi, Mohsen, X. Zhang, Maohua Lin, et al.. (2025). Automated Finite Element Modeling of the Lumbar Spine: A Biomechanical and Clinical Approach to Spinal Load Distribution and Stress Analysis. World Neurosurgery. 201. 124236–124236. 2 indexed citations
3.
Franceschini, Christian, Mohsen Ahmadi, X. Zhang, et al.. (2025). Revolutionizing spine surgery with emerging AI–FEA integration. Journal of Robotic Surgery. 19(1). 615–615.
4.
Liu, Yan, James Doulgeris, Min Shi, et al.. (2024). The Frontiers of Smart Healthcare Systems. Healthcare. 12(23). 2330–2330. 1 indexed citations
5.
Hutchinson, Douglas T., et al.. (2024). Biohybrid Robotic Hand to Investigate Tactile Encoding and Sensorimotor Integration. Biomimetics. 9(2). 78–78. 3 indexed citations
6.
Lin, Maohua, et al.. (2023). Feeling the beat: a smart hand exoskeleton for learning to play musical instruments. Frontiers in Robotics and AI. 10. 1212768–1212768. 10 indexed citations
7.
Hutchinson, Douglas T., et al.. (2022). Multichannel haptic feedback unlocks prosthetic hand dexterity. Scientific Reports. 12(1). 2323–2323. 28 indexed citations
8.
Engeberg, Erik D., et al.. (2021). Human Neuromarkers of Tactile Perception: State of the Art in Methods and Findings. PubMed. 28. 635–639. 1 indexed citations
9.
Lin, Maohua, Morteza Vatani, Jae‐Won Choi, Savaş Dilibal, & Erik D. Engeberg. (2020). Compliant underwater manipulator with integrated tactile sensor for nonlinear force feedback control of an SMA actuation system. Sensors and Actuators A Physical. 315. 112221–112221. 27 indexed citations
10.
Dilibal, Savaş, et al.. (2020). Shape memory alloy tube actuators inherently enable internal fluidic cooling for a robotic finger under force control. Smart Materials and Structures. 29(11). 115009–115009. 15 indexed citations
11.
Engeberg, Erik D., et al.. (2020). Human-Inspired Robotic Eye-Hand Coordination Enables New Communication Channels Between Humans and Robots. International Journal of Social Robotics. 13(5). 1033–1046. 2 indexed citations
12.
Renna, Jordan M., et al.. (2017). Dorsal root ganglia neurite outgrowth measured as a function of changes in microelectrode array resistance. PLoS ONE. 12(4). e0175550–e0175550. 3 indexed citations
13.
Engeberg, Erik D., Savaş Dilibal, Morteza Vatani, Jae‐Won Choi, & John E. Lavery. (2015). Anthropomorphic finger antagonistically actuated by SMA plates. Bioinspiration & Biomimetics. 10(5). 56002–56002. 57 indexed citations
14.
Engeberg, Erik D., et al.. (2014). Human-inspired feedback synergies for environmental interaction with a dexterous robotic hand. Bioinspiration & Biomimetics. 9(4). 46008–46008. 7 indexed citations
15.
Engeberg, Erik D., Morteza Vatani, & Jae‐Won Choi. (2013). Detection of the direction and speed of motion of forces on the surface of a compliant tactile sensor. 158–163. 3 indexed citations
16.
Lavery, John E., et al.. (2012). Biologically inspired grasp primitives for a dexterous robotic hand to catch and lift a sphere. International Conference on Control, Automation and Systems. 1710–1715. 1 indexed citations
17.
Engeberg, Erik D., et al.. (2012). Adaptive synergy control for a dexterous artificial hand based on grasped object orientation. International Conference on Control, Automation and Systems. 1927–1932. 2 indexed citations
18.
Engeberg, Erik D., Morteza Vatani, & Jae‐Won Choi. (2012). Direction of slip detection for a biomimetic tactile sensor. International Conference on Control, Automation and Systems. 1933–1937. 3 indexed citations
19.
Engeberg, Erik D., Sanford G. Meek, & Mark A. Minor. (2008). Hybrid Force–Velocity Sliding Mode Control of a Prosthetic Hand. IEEE Transactions on Biomedical Engineering. 55(5). 1572–1581. 61 indexed citations
20.
Engeberg, Erik D. & Sanford G. Meek. (2008). Improved Grasp Force Sensitivity for Prosthetic Hands Through Force-Derivative Feedback. IEEE Transactions on Biomedical Engineering. 55(2). 817–821. 36 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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