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Enhancing Extended Reality assisted surgery through a Field-of-View video delivery optimization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0196731" target="_blank" >RIV/00216305:26220/26:0196731 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S1389128625000611" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1389128625000611</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Enhancing Extended Reality assisted surgery through a Field-of-View video delivery optimization

  • Original language description

    Emerging Extended Reality (XR) applications bring new opportunities for digital healthcare systems, i.e., eHealth. XR-assisted surgery is one of the most outstanding examples of future technology that has a high social impact on the healthcare and medical educational system. The current work presents the intelligent design for remote XR-assisted surgery. The study presents the Field-of-View (FoV)-based viewport model empowered with behavioral data. It applies the viewport prediction model based on the behavioral data by applying Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). In the final analysis, LSTM showed lower errors and a higher coefficient of determination, but ANN performed much faster. Finally, the study defines the dynamic system’s states for adaptive and fast video delivery concerning Quality of Experience (QoE). The presented approach aims to mitigate the delay to ensure smooth playback and display high-quality images.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

    <a href="/en/project/EH23_021%2F0008829" target="_blank" >EH23_021/0008829: New Technologies for Digital Health</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Computer Networks

  • ISSN

    1389-1286

  • e-ISSN

    1872-7069

  • Volume of the periodical

    March 2025

  • Issue of the periodical within the volume

    259

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    18

  • Pages from-to

  • UT code for WoS article

    001426620700001

  • EID of the result in the Scopus database