Development of Real-time Intra-operative Analysis Software for Brain Activity Using Measured EEG

  • KAJI Yoshio
    Department of Mechanical and Electronic Engineering,Tokushima Bunri University Graduate School of Engineering,The University of Tokushima
  • AKUTAGAWA Masatake
    Department of Electrical and Electronic Engineering,The University of Tokushima
  • SHICHIJO Fumio
    Suzue hospital
  • KINOUCHI Yohsuke
    Department of Electrical and Electronic Engineering,The University of Tokushima
  • NAGAHIRO Shinji
    School of Medicine,The University of Tokushima

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Other Title
  • 術中脳活動リアルタイム解析ソフトウェアの開発
  • ジュッチュウ ノウ カツドウ リアルタイム カイセキ ソフトウェア ノ カイハツ

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In some cases, temporary or permanent occlusion of the arteries that participate in providing cerebral blood flow is needed during surgery. It is important to monitor the brain condition to prevent from a sequela. EEG (electroencephalogram) analysis is one of the most familiar methods. The goal of this study is to develop integrated EEG analysis software. The software consists of data acquisition, waveform memory management, and data analysis components. The advantages of this system are real-time analysis, generality, expandability and portability. At this point in time, it can display waveform, spectrum and topography changes of each frequency component for any electrode group, and DRT (deviation ratio topography) in real time. Moreover, the system warns the operator via alarm when the EEG changes significantly. This function makes it possible to reduce the operator's task, because the operator is able to understand the patient's condition without directly observing the monitoring system. In this study, we also propose the application of moving average-type neural networks (MANN) to analyze the EEG. In this method, the measured EEG is divided into overlapped period of 30 sec. A MANN is trained to predict the EEG using five previous samples in each period. After training, the connecting weights of each MANN are compared using the inner product to evaluate changes in brain condition. According to the results of clinical data analysis, the usefulness of both the MANN analysis and DRT analysis was confirmed.


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