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Building Computational Virtual Reality Environment for Anesthesia

Author

Listed:
  • Wen Xu

    (Nanjing University of Finance and Economic)

  • Jinyuan He

    (Victoria University)

  • Xinyu Cao

    (Victoria University)

  • Peng Zhang

    (Victoria University)

  • Wei Gao

    (Jiangsu Grain and Oil Information Center)

  • Di Pan

    (Jiangsu Grain and Oil Information Center)

  • Yingting Guo

    (Victoria University)

  • Jing He

    (Nanjing University of Finance and Economic
    Victoria University)

Abstract

Traditional anaesthesia training is considered as a time-consuming task since trainees are required to go through an extended period of knowledge learning and practice their skill in the supervision of experienced anaesthetists. In this paper, a Computational Virtual Reality Environment for Anesthesia (CVREA) is proposed, which can significantly improve the training and learning performance of trainee anaesthetists in an efficient way. Virtual reality, big data, data mining and machine learning techniques will be explored and applied in this system. CVREA consists of two main parts: (1) an immersive and interactive VR-based training platform for anaesthetists. It allows trainees to hone their clinical skills in a virtual environment without placing risk to patients. (2) a knowledge learning system which records and collects clinical data with greater richness. Knowledge learning algorithms will be developed to explore these data in order to help data processing and facilitates knowledge discovery in anaesthesiology.

Suggested Citation

  • Wen Xu & Jinyuan He & Xinyu Cao & Peng Zhang & Wei Gao & Di Pan & Yingting Guo & Jing He, 2016. "Building Computational Virtual Reality Environment for Anesthesia," Annals of Data Science, Springer, vol. 3(4), pages 413-421, December.
    • Handle: RePEc:spr:aodasc:v:3:y:2016:i:4:d:10.1007_s40745-016-0089-5
    DOI: 10.1007/s40745-016-0089-5
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