A. Yu. Meigal

997 total citations
83 papers, 733 citations indexed

About

A. Yu. Meigal is a scholar working on Biomedical Engineering, Neurology and Physiology. According to data from OpenAlex, A. Yu. Meigal has authored 83 papers receiving a total of 733 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Biomedical Engineering, 21 papers in Neurology and 19 papers in Physiology. Recurrent topics in A. Yu. Meigal's work include Muscle activation and electromyography studies (32 papers), Neurological disorders and treatments (18 papers) and Parkinson's Disease Mechanisms and Treatments (17 papers). A. Yu. Meigal is often cited by papers focused on Muscle activation and electromyography studies (32 papers), Neurological disorders and treatments (18 papers) and Parkinson's Disease Mechanisms and Treatments (17 papers). A. Yu. Meigal collaborates with scholars based in Russia, Finland and France. A. Yu. Meigal's co-authors include Pasi A. Karjalainen, Saara M. Rissanen, Olavi Airaksinen, Markku Kankaanpää, Mika P. Tarvainen, Dmitry Korzun, Ina M. Tarkka, Hannu Rintamäki, Juha Oksa and Juho Nuutinen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Physiology and IEEE Transactions on Biomedical Engineering.

In The Last Decade

A. Yu. Meigal

76 papers receiving 716 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Yu. Meigal Russia 13 299 257 172 112 111 83 733
Saara M. Rissanen Finland 14 321 1.1× 366 1.4× 50 0.3× 136 1.2× 147 1.3× 41 759
John A. Burne Australia 15 212 0.7× 276 1.1× 58 0.3× 112 1.0× 159 1.4× 29 579
Martin E. Héroux Australia 18 332 1.1× 192 0.7× 40 0.2× 268 2.4× 172 1.5× 52 900
Michel Gauthier Canada 10 355 1.2× 124 0.5× 49 0.3× 302 2.7× 199 1.8× 18 813
Erika G. Spaich Denmark 15 486 1.6× 87 0.3× 98 0.6× 213 1.9× 73 0.7× 58 915
S.L. Lehman United States 12 270 0.9× 69 0.3× 82 0.5× 201 1.8× 33 0.3× 27 668
Franz Marxreiter Germany 20 259 0.9× 741 2.9× 153 0.9× 68 0.6× 377 3.4× 42 1.4k
Raif Çakmur Türkiye 15 72 0.2× 334 1.3× 70 0.4× 422 3.8× 102 0.9× 42 1.0k
Dan Stashuk Canada 7 372 1.2× 56 0.2× 43 0.3× 209 1.9× 103 0.9× 7 514
Carlo Maremmani Italy 14 237 0.8× 467 1.8× 100 0.6× 75 0.7× 95 0.9× 28 844

Countries citing papers authored by A. Yu. Meigal

Since Specialization
Citations

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

Fields of papers citing papers by A. Yu. Meigal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Yu. Meigal. 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 A. Yu. Meigal. The network helps show where A. Yu. Meigal may publish in the future.

Co-authorship network of co-authors of A. Yu. Meigal

This figure shows the co-authorship network connecting the top 25 collaborators of A. Yu. Meigal. A scholar is included among the top collaborators of A. Yu. Meigal 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 A. Yu. Meigal. A. Yu. Meigal 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.
Meigal, A. Yu., et al.. (2023). Assessment of Stress Level with Help of “Smart Clothing” Sensors, Heart Rate Variability-Based Markers and Machine Learning Algorithms. SHILAP Revista de lepidopterología. 20–20. 1 indexed citations
2.
Meigal, A. Yu., et al.. (2022). Motor Activity Sensorics for mHealth Support of Human Resilience in Daily Life. SHILAP Revista de lepidopterología. 169–177. 3 indexed citations
3.
Meigal, A. Yu., et al.. (2021). Vertical Spatial Orientation in Patients with Parkinsonism under the State of Single “Dry” Immersion and a Course of Immersions. Human Physiology. 47(2). 183–192. 3 indexed citations
4.
Meigal, A. Yu., et al.. (2021). Program of Seven 45-min Dry Immersion Sessions Improves Choice Reaction Time in Parkinson’s Disease. Frontiers in Physiology. 11. 621198–621198. 7 indexed citations
5.
Meigal, A. Yu., et al.. (2021). Autonomic Function in Parkinson's Disease Subjects Across Repeated Short-Term Dry Immersion: Evidence From Linear and Non-linear HRV Parameters. Frontiers in Physiology. 12. 712365–712365. 9 indexed citations
6.
Meigal, A. Yu., et al.. (2021). Postactivation Effect in the Deltoid Muscle of Healthy Young Subjects after a Short-Term “Dry” Immersion. Human Physiology. 47(3). 289–295. 3 indexed citations
7.
Meigal, A. Yu., et al.. (2018). Ambient Intelligence Based Vision to At-Home Laboratory for Personalized Monitoring and Assessment of Motion-Cognitive State in Elderly. SHILAP Revista de lepidopterología. 52. 159–165. 2 indexed citations
8.
Meigal, A. Yu., et al.. (2016). Heart Rate Variability Predicts the Ovulation in Young Women: Possible Implications for Mobile Medicine Services. SHILAP Revista de lepidopterología. 1 indexed citations
9.
Meigal, A. Yu., et al.. (2015). Development of an Infant’s Peripheral Motor System Within the First 3 Years of Life as Studied Using Surface Electromyography. SHILAP Revista de lepidopterología. 12(3). 277–277. 1 indexed citations
10.
Meigal, A. Yu., et al.. (2015). HEART RATE VARIABILITY IN WOMEN DURING VARIOUS SEASONS AND PHASES OF THE MENSTRUAL CYCLE. Ekologiya Cheloveka (Human Ecology). 22(2). 20–26. 2 indexed citations
11.
Meigal, A. Yu., et al.. (2015). Nonlinear parameters of surface EMG in schizophrenia patients depend on kind of antipsychotic therapy. Frontiers in Physiology. 6. 197–197. 8 indexed citations
12.
13.
Meigal, A. Yu., et al.. (2014). EMG signal morphology and kinematic parameters in essential tremor and Parkinson’s disease patients. Journal of Electromyography and Kinesiology. 24(2). 300–306. 40 indexed citations
14.
Meigal, A. Yu., Saara M. Rissanen, Mika P. Tarvainen, et al.. (2013). Non-Linear EMG Parameters for Differential and Early Diagnostics of Parkinson’s Disease. Frontiers in Neurology. 4. 135–135. 40 indexed citations
15.
Meigal, A. Yu., et al.. (2013). Influence of postconceptual age on the electromyographic characteristics in newborns. Human Physiology. 39(3). 278–283. 3 indexed citations
16.
Meigal, A. Yu.. (2012). Synergistic action of gravity and temperature on the motor system within the lifespan: A “Baby Astronaut” hypothesis. Medical Hypotheses. 80(3). 275–283. 11 indexed citations
17.
Meigal, A. Yu.. (2011). Ontogenetic model of gravity and weightlessness: Theoretical and applied aspects. Human Physiology. 37(6). 755–762. 2 indexed citations
18.
Rissanen, Saara M., Markku Kankaanpää, Mika P. Tarvainen, et al.. (2010). Discrimination of EMG and acceleration measurements between patients with Parkinson's disease and healthy persons. PubMed. 2010. 4878–4881. 6 indexed citations
19.
Meigal, A. Yu., Saara M. Rissanen, Mika P. Tarvainen, et al.. (2008). Novel parameters of surface EMG in patients with Parkinson’s disease and healthy young and old controls. Journal of Electromyography and Kinesiology. 19(3). e206–e213. 94 indexed citations
20.
Meigal, A. Yu., et al.. (2002). Electromyographic Parameters of Muscle Fatigue in Patients with Parkinsonism. Human Physiology. 28(4). 448–453. 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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