KFU. Card publication. Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices

KAZAN
FEDERAL UNIVERSITY

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FUZZY CONTROL MODEL TO DETERMINE THE SCORE IN VIRTUAL REALITY-BASED APPENDECTOMY PRACTICES

Form of presentation

Articles in international journals and collections

Year of publication

2021

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Authors, employees of KFU

Kugurakova Vlada Vladimirovna, author

Other authors

Madrigal Omar Correa , author

Vega Alieski Veliz , author

Bibliographic description in the original language

Vega, A.V., Madrigal, O.C., & Kugurakova, V.V. Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices // Lecture Notes in Networks and Systems. 2021. Vol.232. P. 899-906.

Annotation

Virtual Reality simulators allow surgical training in a safe and controlled environment. Through simulation, procedures can be repeated until a certain level of skill is acquired. This paper presents a fuzzy logic model implemented separately from the Virtual Reality simulator so that it can be used from other simulators. Multiple linear regression is applied for training using a Python library. The model is part of a self-adaptive model for a Virtual Reality-based surgery simulator. ? 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Appendectomy, Fuzzy logic, Surgery, Virtual reality

The name of the journal

Lecture Notes in Networks and Systems

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=260860&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Kugurakova Vlada Vladimirovna	ru_RU
dc.contributor.author	Madrigal Omar Correa	ru_RU
dc.contributor.author	Vega Alieski Veliz	ru_RU
dc.date.accessioned	2021-01-01T00:00:00Z	ru_RU
dc.date.available	2021-01-01T00:00:00Z	ru_RU
dc.date.issued	2021	ru_RU
dc.identifier.citation	Vega, A.V., Madrigal, O.C., & Kugurakova, V.V. Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices // Lecture Notes in Networks and Systems. 2021. Vol.232. P. 899-906.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=260860&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Networks and Systems	ru_RU
dc.description.abstract	Virtual Reality simulators allow surgical training in a safe and controlled environment. Through simulation, procedures can be repeated until a certain level of skill is acquired. This paper presents a fuzzy logic model implemented separately from the Virtual Reality simulator so that it can be used from other simulators. Multiple linear regression is applied for training using a Python library. The model is part of a self-adaptive model for a Virtual Reality-based surgery simulator. ? 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Appendectomy	ru_RU
dc.subject	Fuzzy logic	ru_RU
dc.subject	Surgery	ru_RU
dc.subject	Virtual reality	ru_RU
dc.title	Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices	ru_RU
dc.type	Articles in international journals and collections	ru_RU