Victor Anisimov

Dr. Victor Anisimov

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Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Journal Article
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KBKsenia Babanova
Ksenia Babanova
ARArsen Revazov
Arsen Revazov
KCKonstantin Chernozatonskiy
Konstantin Chernozatonskiy
APAndrey Pikunov
Andrey Pikunov
Victor AnisimovVictor Anisimov
Victor Anisimov
The growing interest in evaluating the reader's comprehension leads to the search for new methods that allow such estimation in real-time (or pseudo-real-time). This can be used for more effective educational processes and to adopt textual content for various purposes. The present study used the Oken Reader eye-tracking application (60 Hz) for mass-market devices to assess reading comprehension processes. Twenty-three (23) respondents aged between 19 and 31 (mean = 24. 5, SE = 1. 4, 65% female) participated in the study. The mean, mu, and sigma parameters differed significantly depending on the level of text comprehension. This result indicates the possibility of using mass-market devices with eye-tracking technology to assess comprehension in reading. Furthermore, the study's results confirm the possibility of searching the correlations between physiological indicators such as eye movements and comprehension.

15 September 2016 in I.P. Pavlov Russian Medical Biological Herald
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Marina ShurupovaMarina Shurupova
Marina Shurupova
Victor AnisimovVictor Anisimov
Victor Anisimov
ALAlexander Latanov
Alexander Latanov
VKV N Kasatkin
V N Kasatkin
The review relates to modern point of view on the role of cerebellar structures in eye movement control. The review dedicates todisorders of all types of eye movements involving participating cerebellum in oculomotor and vestibular systems which are supported by experimental results. Revealing the mechanisms of eye movement disorders, especially when gaze-holding and saccadic movements, opens possibilities for its therapy.

27 November 2019 in Neuroscience and Behavioral Physiology
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MKM. V. Konstantinova
M. V. Konstantinova
Victor AnisimovVictor Anisimov
Victor Anisimov
LTL. V. Tereshchenko
L. V. Tereshchenko
ALAlexander Latanov
Alexander Latanov

18 April 2021
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KSKsenia Shedenko
Ksenia Shedenko
Victor AnisimovVictor Anisimov
Victor Anisimov
AKAnastasia Kovaleva
Anastasia Kovaleva
ALAlexander Latanov
Alexander Latanov

20 August 2021 in Applied Sciences
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DSDmitry Skvortsov
Dmitry Skvortsov
Victor AnisimovVictor Anisimov
Victor Anisimov
AAAlina Aizenshtein
Alina Aizenshtein
The biomechanics of military crawl locomotion is poorly covered in scientific literature so far. Crawl locomotion may be used as a testing procedure which allows for the detection of not only obvious, but also hidden locomotor dysfunctions. The aim of the study was to investigate the biomechanics of crawling among healthy adult participants. Eight healthy adults aged 15–31 (four women and four men) were examined by means of a 3D kinematic analysis with Optitrack optical motion-capture system which consists of 12 Flex 13 cameras. The movements of the shoulder, elbow, knee, and hip joints were recorded. A person was asked to crawl 4 m on his/her belly. The obtained results including space-time data let us characterize military crawling in terms of pelvic and lower limb motions as a movement similar to walking but at a more primitive level. Progressive and propulsive motions are characterized as normal; additional right–left side motions—with high degree of reciprocity. It was found that variability of the left-side motions is significantly lower than that of the right side (Z = 4.49, p < 0.0001). The given normative data may be used as a standard to estimate the test results for patients with various pathologies of motor control (ataxia, abasia, etc.).

10 October 2024 in Russian Journal of Information Technology in Sports
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AKAnastasia Kovaleva
Anastasia Kovaleva
Victor AnisimovVictor Anisimov
Victor Anisimov
Introduction. The rhythm of the heart (heart rate, HR) is closely related to the rhythm of breathing. The phenomenon of respiratory sinus arrhythmia (an increase in heart rate during inhalation and a decrease during exhalation) is well known. Cardiorespiratory interactions and synchronization of these two signals are evaluated differently in the literature. The purpose of this work was to propose and test an approach to assess cardiorespiratory synchronization – the calculation of the cross-correlation coefficient between heart rate and respiration curve, for a more objective characterization of an athlete’s bodily states. Methods. A photoplethysmogram and respiration were recorded in 45 healthy athletes (18-25 years old) in three situations: rest, paced breathing at 6 times per minute (resonant frequency) and the performance of a sensorimotor task (tapping with the rhythmic metronome sounds and then reproducing a given rhythm from memory). For the HR and respiration curves, filtering and smoothing algorithms using the Savitsky-Goley method were applied sequentially, and then the cross-correlation coefficient between the two curves was calculated. The spectral parameters of heart rate variability (LF and HF) were also obtained, since during spontaneous breathing its contribution to the HR is reflected in HF band, and when breathing at a resonant frequency, a peak occurs at a frequency of 0.1 Hz in the LF band. Results. The cross-correlation coefficient, as well as the peak of HR spectral power at 0.1 Hz, increases significantly when breathing at a resonant frequency. The relationship between these indicators is most accurately described not by a linear, but by a logarithmic dependence. When performing a sensorimotor task, the so-called respiratory waves in the heart rhythm spectrum (HF) do not change from rest to tapping by a metronome and then to holding the rhythm by memory. At the same time, the cross-correlation coefficient demonstrates significant changes between these situations. In addition, a significant correlation was found between the change in the cross-correlation coefficient and the stability of rhythm maintenance (from memory): an increase in the cardiorespiratory synchronization leads to a decrease in motor rhythm stability. Conclusion. Assessment of cardiorespiratory synchronization due to the peculiarities of both signals (changes in heart rate and respiratory phases) requires preliminary preparation of data arrays: filtering and smoothing the stepped curve of heart rate dynamics. The calculation of the cross-correlation coefficient can be used to assess cardiorespiratory synchronization in real time and is likely to be applicable in short time fragments to assess emotional reactions and other short-term fluctuations in psychophysiological conditions, where the classical method of assessing changes in heart rhythm in the frequency or time domains is not applicable.