Evaluation of shoulder joint data obtained from con-trex medical system | Научно-инновационный портал СФУ

Evaluation of shoulder joint data obtained from con-trex medical system

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 12th KES International Conference on Intelligent Decision Technologies, KES-IDT 2020

Год издания: 2020

Идентификатор DOI: 10.1007/978-981-15-5925-9_13

Ключевые слова: arthrokinematics, biomechanics, con-trex, correlation analysis, histogram approach, nonlinear regression, numerical data modeling, robotic mechanotherapy, shoulder joint, visualization

Аннотация: The study of the kinematic patterns, as well as, their variability in normal and pathological conditions is an urgent task and is actively carried out in biomechanics, rehabilitation, and sports medicine. One of aspects is the evaluation of data obtained in the framework of the use of robotic mechanotherapy at the CON-TREX medical system during rehabilitation treatment of patients after arthroscopic reconstructive surgery on the shoulder joint. The work shows steps of processing and analyzing CON-TREX medical systems data. The analysis of statistics and modeling of data obtained during the exercise of the patient using the CON-TREX system are performed. For this, a correlation analysis of the data is applied and the Pearson correlation coefficients are calculated. The relationship between the variables represented by the data series is revealed. Improving the visual presentation for the entire set of CON-TREX clinical data with the help of approximations, as well as, within the framework of the histogram approach allows to increase the accuracy of diagnostic evaluations. The data analysis as part of a study of the dynamics shows a number of dependencies in indicators that allow to more accurately plan the exercise cycle for the patient. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2020.

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Издание

Журнал: Smart Innovation, Systems and Technologies

Выпуск журнала: Vol. 193

Номера страниц: 155-165

ISSN журнала: 21903018

Авторы

  • Zotin A. (Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy pr 31, Krasnoyarsk, 660037, Russian Federation)
  • Simonov K. (Institute of Computational Modeling SB RAS, 50/44 Akademgorodok, Krasnoyarsk, 660036, Russian Federation)
  • Kabaev E. (Center for Restorative Medicine of FSRCC FMBA Russian Federation, 25b Biathlonnaya st, Krasnoyarsk, 660041, Russian Federation)
  • Kurako M. (Siberian Federal University, 26 Kirensky st, Krasnoyarsk, 660074, Russian Federation)
  • Matsulev A. (Institute of Computational Modeling SB RAS, 50/44 Akademgorodok, Krasnoyarsk, 660036, Russian Federation)

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