dc.contributor.author |
Vega A.V. |
|
dc.contributor.author |
Madrigal O.C. |
|
dc.contributor.author |
Kugurakova V. |
|
dc.date.accessioned |
2022-02-09T20:48:25Z |
|
dc.date.available |
2022-02-09T20:48:25Z |
|
dc.date.issued |
2021 |
|
dc.identifier.issn |
2367-3370 |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/170421 |
|
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. |
|
dc.relation.ispartofseries |
Lecture Notes in Networks and Systems |
|
dc.subject |
Appendectomy |
|
dc.subject |
Fuzzy logic |
|
dc.subject |
Surgery |
|
dc.subject |
Virtual reality |
|
dc.title |
Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices |
|
dc.type |
Conference Proceeding |
|
dc.relation.ispartofseries-volume |
232 LNNS |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
899 |
|
dc.source.id |
SCOPUS23673370-2021-232-SID85120581541 |
|