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A critical care monitoring system for depth of anaesthesia analysis based on entropy analysis and physiological information database

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Abstract

Diagnosis of depth of anaesthesia (DoA) plays an important role in treatment and drug usage in the operating theatre and intensive care unit. With the flourishing development of analysis methods and monitoring devices for DoA, a small amount of physiological data had been stored and shared for further researches. In this paper, a critical care monitoring (CCM) system for DoA monitoring and analysis was designed and developed, which includes two main components: a physiologic information database (PID) and a DoA analysis subsystem. The PID, including biologic data and clinical information was constructed through a browser and server model so as to provide a safe and open platform for storage, sharing and further study of clinical anaesthesia information. In the analysis of DoA, according to our previous studies on approximate entropy, sample entropy (SampEn) and multi-scale entropy (MSE), the SampEn and MSE were integrated into the subsystem for indicating the state of patients underwent surgeries in real time because of their stability. Therefore, this CCM system not only supplies the original biological data and information collected from the operating room, but also shares our studies for improvement and innovation in the research of DoA.

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Acknowledgments

The authors wish to thank the exchange master student program of Yuan Ze University in Taiwan and Wuhan University of Technology in China for supporting this research. This research was supported by the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by the Ministry of Science and Technology (Grant Number: NSC 102-2911-I-008-001). Also, it was supported by National Chung-Shan Institute of Science and Technology in Taiwan (Grant Numbers: CSIST-095-V301 and CSIST-095-V302). Moreover, this work was supported by the Keygrant Project of Chinese Ministry of Education (Grant No. 313042), the Key Project of Natural Science Foundation of Hubei Province of China (Grant No. 2013CFA044).

Conflict of interest

The authors declare no conflict of interests.

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Authors and Affiliations

  1. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Qin Wei

  2. School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Yang Li & Quan Liu

  3. Department of Anesthesiology, College of Medicine, National Taiwan University, Taipei, 100, Taiwan

    Shou-Zen Fan

  4. School of Engineering and Design, Brunel University, London, UB8 3PH, UK

    Maysam F. Abbod

  5. Department of Anesthesiology, Far Eastern Memorial Hospital, Ban-Chiao, Taiwan

    Cheng-Wei Lu & Tzu-Yu Lin

  6. Department of Mechanical Engineering, and Innovation Center for Big Data and Digital Convergence, Yuan Ze University, 135, Yuan-Tung Road, Chung-Li, 32003, Taiwan

    Cheng-Wei Lu, Tzu-Yu Lin & Jiann-Shing Shieh

  7. National Chung-Shan Institute of Science and Technology, Longtan, Taoyuan, Taiwan

    Kuo-Kuang Jen & Shang-Ju Wu

  8. Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chung-Li, 32001, Taiwan

    Jiann-Shing Shieh

Authors
  1. Qin Wei
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  2. Yang Li
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  3. Shou-Zen Fan
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  4. Quan Liu
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Corresponding author

Correspondence to Jiann-Shing Shieh.

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Wei, Q., Li, Y., Fan, SZ. et al. A critical care monitoring system for depth of anaesthesia analysis based on entropy analysis and physiological information database. Australas Phys Eng Sci Med 37, 591–605 (2014). https://doi.org/10.1007/s13246-014-0285-6

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  • DOI: https://doi.org/10.1007/s13246-014-0285-6

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