Elnaz Lashgari

441 total citations · 1 hit paper
8 papers, 289 citations indexed

About

Elnaz Lashgari is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine and Physiology. According to data from OpenAlex, Elnaz Lashgari has authored 8 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 3 papers in Cardiology and Cardiovascular Medicine and 3 papers in Physiology. Recurrent topics in Elnaz Lashgari's work include EEG and Brain-Computer Interfaces (3 papers), Spaceflight effects on biology (2 papers) and Muscle activation and electromyography studies (2 papers). Elnaz Lashgari is often cited by papers focused on EEG and Brain-Computer Interfaces (3 papers), Spaceflight effects on biology (2 papers) and Muscle activation and electromyography studies (2 papers). Elnaz Lashgari collaborates with scholars based in United States and Iran. Elnaz Lashgari's co-authors include Uri Maoz, Aman Mahajan, Babak Hossein Khalaj, Siamak Salavatian, Mehran Jahed, Emel Demircan, Kimberly Howard‐Quijano and Erica A. Dale and has published in prestigious journals such as PLoS ONE, Anesthesiology and Journal of Neuroscience Methods.

In The Last Decade

Elnaz Lashgari

7 papers receiving 283 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Data augmentation for deep-learning-based electroencephalography

2020 266 citations Elnaz Lashgari, Uri Maoz et al. Journal of Neuroscience Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elnaz Lashgari United States	4	191	52	50	41	40	8	289
Chamandeep Kaur India	7	243 1.3×	61 1.2×	71 1.4×	28 0.7×	37 0.9×	14	336
Trilok Chand India	7	199 1.0×	65 1.3×	36 0.7×	45 1.1×	30 0.8×	19	373
Nannapas Banluesombatkul Thailand	3	209 1.1×	39 0.8×	42 0.8×	25 0.6×	29 0.7×	6	259
Padmavati Khandnor India	10	204 1.1×	64 1.2×	67 1.3×	48 1.2×	30 0.8×	28	444
Chong Liu China	10	216 1.1×	34 0.7×	36 0.7×	20 0.5×	45 1.1×	30	298
Hubert Banville Canada	10	285 1.5×	48 0.9×	62 1.2×	38 0.9×	37 0.9×	16	373
Xiaolin Hong China	7	191 1.0×	26 0.5×	40 0.8×	54 1.3×	30 0.8×	12	317
Phattarapong Sawangjai Thailand	6	299 1.6×	55 1.1×	76 1.5×	52 1.3×	58 1.4×	10	402
A. Saidatul Malaysia	9	224 1.2×	68 1.3×	61 1.2×	50 1.2×	31 0.8×	40	327
Xinlin Sun China	11	214 1.1×	36 0.7×	35 0.7×	45 1.1×	34 0.8×	23	312

Countries citing papers authored by Elnaz Lashgari

Since Specialization

Citations

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

Fields of papers citing papers by Elnaz Lashgari

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elnaz Lashgari

This figure shows the co-authorship network connecting the top 25 collaborators of Elnaz Lashgari. A scholar is included among the top collaborators of Elnaz Lashgari 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 Elnaz Lashgari. Elnaz Lashgari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Lashgari, Elnaz, et al.. (2025). A systematic review of flotation-restricted environmental stimulation therapy (REST). BMC Complementary Medicine and Therapies. 25(1). 230–230.

2.

Lashgari, Elnaz, et al.. (2023). A systematic review of Flotation-Restricted Environmental Stimulation Therapy (REST). medRxiv. 3 indexed citations

3.

Lashgari, Elnaz & Uri Maoz. (2021). Dimensionality reduction for classification of object weight from electromyography. PLoS ONE. 16(8). e0255926–e0255926. 6 indexed citations

4.

Salavatian, Siamak, Uri Maoz, Elnaz Lashgari, et al.. (2021). Spinal Anesthesia Reduces Myocardial Ischemia–triggered Ventricular Arrhythmias by Suppressing Spinal Cord Neuronal Network Interactions in Pigs. Anesthesiology. 134(3). 405–420. 10 indexed citations

5.

Lashgari, Elnaz, et al.. (2020). Data augmentation for deep-learning-based electroencephalography. Journal of Neuroscience Methods. 346. 108885–108885. 266 indexed citations breakdown →

6.

Lashgari, Elnaz & Emel Demircan. (2017). Electromyography Pattern Classification With Laplacian Eigenmaps In Human Running. Zenodo (CERN European Organization for Nuclear Research). 11(4). 412–417. 1 indexed citations

7.

Lashgari, Elnaz, et al.. (2013). Method as a preprocessing stage for tracking sperms progressive motility. 290. 170–174. 1 indexed citations

8.

Lashgari, Elnaz, Mehran Jahed, & Babak Hossein Khalaj. (2013). Manifold learning for ECG arrhythmia recognition. 1. 126–131. 2 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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