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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/77459

    Title: 類神經網路暨圖形辨識之腦波判讀系統;The Interpretation System of the Brain Wave(EEG) by Artificial Neural Network and Pattern Recognition
    Authors: 劉景浩;Liu, Ching-Hao
    Contributors: 照明與顯示科技研究所
    Keywords: 腦波;大腦科學;類神經網路;圖形辨識
    Date: 2018-07-23
    Issue Date: 2018-08-31 14:43:16 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究主要利用圖形辨識及類神經網路兩大技術來分析、解讀、與學習腦波訊號,進而判讀受測者的想法。研究先以高精度腦波儀 OpenBCI進行量測,擷取八個波段的生理腦波電訊號,接著以Google的開源API-Teachable Machine來訓練系統,經學習後不僅可以判斷受測者的精神狀態為專注亦或是放鬆,此外還能分辨受測者是在想左邊還右邊。此研究成果在腦波的判讀技術上可視為一重大發展。;This study based on two major technologies: Artificial Neural netw-ork and pattern recognition. By using these technologies, we can analyze, interpret, and learn brainwave signals; furthermore, interpret the subject′s thoughts. At first, the study measured with a high-precision electroencep-halogram OpenBCI and captured eight wavebands of physiological brain-wave signals. Then we use Google′s open source API-Teachable Machine to train the system recognizing brainwave pattern. After learning, it can n-ot only distinguish between focused and relaxed from the subject′s mental state, but also distinguish between left and right from the subject′s thinki-ng. This research result can be regarded as a major development in the in-terpretation of brain science.
    Appears in Collections:[照明與顯示科技研究所 ] 博碩士論文

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