Sahar Moghimi

968 total citations
52 papers, 651 citations indexed

About

Sahar Moghimi is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Occupational Therapy. According to data from OpenAlex, Sahar Moghimi has authored 52 papers receiving a total of 651 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 13 papers in Biomedical Engineering and 7 papers in Occupational Therapy. Recurrent topics in Sahar Moghimi's work include EEG and Brain-Computer Interfaces (18 papers), Neural dynamics and brain function (15 papers) and Muscle activation and electromyography studies (9 papers). Sahar Moghimi is often cited by papers focused on EEG and Brain-Computer Interfaces (18 papers), Neural dynamics and brain function (15 papers) and Muscle activation and electromyography studies (9 papers). Sahar Moghimi collaborates with scholars based in Iran, France and Canada. Sahar Moghimi's co-authors include Hadi Kalani, Alireza Akbarzadeh, Abbas Ebrahimi-Moghadam, Fabrice Wallois, Mahdi Mahmoudzadeh, Fatemeh Hasanzadeh, Mohsen Annabestani, Iman Parisay, David Elad and H. Zamiri‐Jafarian and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Sahar Moghimi

51 papers receiving 630 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sahar Moghimi Iran 16 387 121 112 74 54 52 651
Andrea Bandini Italy 15 113 0.3× 63 0.5× 72 0.6× 105 1.4× 20 0.4× 46 749
Kun Chen China 13 364 0.9× 114 0.9× 79 0.7× 78 1.1× 12 0.2× 60 557
Ali Maleki Iran 11 188 0.5× 166 1.4× 77 0.7× 24 0.3× 27 0.5× 59 409
Simone Spagnol Italy 14 446 1.2× 87 0.7× 136 1.2× 215 2.9× 27 0.5× 57 573
David Perpetuini Italy 22 213 0.6× 309 2.6× 124 1.1× 24 0.3× 89 1.6× 65 954
Philip W. Fink New Zealand 17 632 1.6× 229 1.9× 87 0.8× 60 0.8× 314 5.8× 62 1.2k
Matthias Lochmann Germany 14 372 1.0× 151 1.2× 31 0.3× 23 0.3× 34 0.6× 27 765
Matteo Spezialetti Italy 17 341 0.9× 121 1.0× 213 1.9× 42 0.6× 100 1.9× 36 782
Zhichuan Tang China 14 442 1.1× 421 3.5× 38 0.3× 77 1.0× 52 1.0× 38 894
Andrea Biasiucci Switzerland 7 671 1.7× 224 1.9× 34 0.3× 32 0.4× 27 0.5× 13 822

Countries citing papers authored by Sahar Moghimi

Since Specialization
Citations

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

Fields of papers citing papers by Sahar Moghimi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sahar Moghimi

This figure shows the co-authorship network connecting the top 25 collaborators of Sahar Moghimi. A scholar is included among the top collaborators of Sahar Moghimi 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 Sahar Moghimi. Sahar Moghimi 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.
Querné, Laurent, et al.. (2024). Negative central activity in extremely preterm newborns: EEG characterization and relationship with brain injuries and neurodevelopmental outcome. Clinical Neurophysiology. 163. 236–243. 1 indexed citations
2.
Wallois, Fabrice, et al.. (2024). Auditory Rhythm Encoding during the Last Trimester of Human Gestation: From Tracking the Basic Beat to Tracking Hierarchical Nested Temporal Structures. Journal of Neuroscience. 45(4). e0398242024–e0398242024. 2 indexed citations
3.
Wallois, Fabrice, et al.. (2023). Rhythm in the Premature Neonate Brain: Very Early Processing of Auditory Beat and Meter. Journal of Neuroscience. 43(15). 2794–2802. 16 indexed citations
4.
Fiveash, Anna, Laura Ferreri, Fleur L. Bouwer, et al.. (2023). Can rhythm-mediated reward boost learning, memory, and social connection? Perspectives for future research. Neuroscience & Biobehavioral Reviews. 149. 105153–105153. 23 indexed citations
5.
Mahmoudzadeh, Mahdi, et al.. (2022). Evolution of cross-frequency coupling between endogenous oscillations over the temporal cortex in very premature neonates. Cerebral Cortex. 33(2). 278–289. 3 indexed citations
6.
Mahmoudzadeh, Mahdi, et al.. (2022). Preterm neonates distinguish rhythm violation through a hierarchy of cortical processing. Developmental Cognitive Neuroscience. 58. 101168–101168. 10 indexed citations
7.
Moghimi, Sahar, et al.. (2020). The Investigation of Simultaneous EEG and Eye Tracking Characteristics During Fixation Task in Mild Alzheimer’s Disease. Clinical EEG and Neuroscience. 52(3). 211–220. 8 indexed citations
8.
Wallois, Fabrice, et al.. (2020). Back to basics: the neuronal substrates and mechanisms that underlie the electroencephalogram in premature neonates. Neurophysiologie Clinique. 51(1). 5–33. 41 indexed citations
9.
Hasanzadeh, Fatemeh, Mohsen Annabestani, & Sahar Moghimi. (2019). Continuous Emotion Recognition during Music Listening Using EEG Signals:\n A Fuzzy Parallel Cascades Model. arXiv (Cornell University). 27 indexed citations
10.
Moghimi, Sahar, et al.. (2019). Slow spindles are associated with cortical high frequency activity. NeuroImage. 189. 71–84. 21 indexed citations
11.
Moghimi, Sahar, et al.. (2019). Detection of reaching intention using EEG signals and nonlinear dynamic system identification. Computer Methods and Programs in Biomedicine. 175. 151–161. 7 indexed citations
12.
Nemati, Samaneh, et al.. (2019). Lost in music: Neural signature of pleasure and its role in modulating attentional resources. Brain Research. 1711. 7–15. 21 indexed citations
13.
14.
Moghimi, Sahar, et al.. (2017). Culture Modulates the Brain Response to Harmonic Violations: An EEG Study on Hierarchical Syntactic Structure in Music. Frontiers in Human Neuroscience. 11. 591–591. 8 indexed citations
15.
Moghimi, Sahar, et al.. (2017). Application of an ANN-GA Method for Predicting the Biting Force Using Electromyogram Signals. 14(1). 41–52. 2 indexed citations
16.
Kalani, Hadi, Alireza Akbarzadeh, & Sahar Moghimi. (2015). A Hybrid Neural Network Approach for Kinematic Modeling of a Novel 6-UPS Parallel Human-Like Mastication Robot. SHILAP Revista de lepidopterología. 12(4). 251–261. 6 indexed citations
17.
Moghimi, Sahar, et al.. (2014). Design and Evaluation of a Pressure and Temperature Monitoring System for Pressure Ulcer Prevention. SHILAP Revista de lepidopterología. 6 indexed citations
18.
Moghimi, Sahar, et al.. (2011). Design and implementation of a hybrid genetic algorithm and artificial neural network system for predicting the sizes of unerupted canines and premolars. European Journal of Orthodontics. 34(4). 480–486. 28 indexed citations
19.
Moghimi, Sahar, et al.. (2011). Automatic evaluation of pressure sore status by combining information obtained from high-frequency ultrasound and digital photography. Computers in Biology and Medicine. 41(7). 427–434. 9 indexed citations
20.

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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