基於錯誤相關電位應用於線上與非線上混合腦機介面系統

Offline and online approaches for hybrid brain-machine interfaces based on error-related potentials

馬羅奈斯本(Mauro Nascimben)

指導教授 ： 方偉騏

國立交通大學/電機學院/電機資訊國際學位學程/碩士(2018年)

摘要

錯誤相關電位是一種應用於混合腦機介面系統情境的調控機制，主要功能為增強人機介面的效能。當受測者發生識別錯誤的時候自然會出現因錯誤相關電位而誘導的腦電波。本論文針對錯誤相關電位，使用不同的技術及方法進行探討。在非線上眾多分類方法，多種類的分類器被拿來與線上遞歸神經網絡和支持向量機比較，並進行單次試驗的基礎上應用。根據調查以及實驗數據結果顯示，非線上分類為基礎的脈衝序列卷積尖峰神經網絡，應用在錯誤相關電位，有極好的正相關結果。

關鍵字

腦電腦界面 ； 腦電圖

並列摘要

Error Related Potentials could be used in Hybrid Brain Computer Interfaces systems as control mechanism to improve the human-machine interaction. Error Related Potentials are naturally elicited brainwaves when a subject recognizes a mistake. In this thesis Error Related Potentials detection is explored using different techniques and approaches. In an offline classification methodology various classifiers are compared while for online detection recurrent neural network and support vector machine are applied on single-trial basis. For offline classification a spiking neural network based on convolution of spike trains is investigated showing a promising positive outcome in detecting Error Related brainwaves

並列關鍵字

Brain Computer Interface ； electroencephalography

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