新型可移動與穿戴式之無線腦機電路設計與實驗驗證

Abstract

通過腦電圖（EEG）的方法了解大腦功能始終是一個重要的問題對於分析腦中樞神經系統。許多腦電訊號的採集是利用腦機介面（BCI）系統來實現，但其龐大的設備和濕式感測電極的使用會造成不舒服而且為使用者帶來不便。因此，為了克服上述傳統的BCI系統的局限性限制，在這項研究中提出了一個無線可穿戴式多通道腦電BCI系統，包括無線訊號採集設備，彈簧乾式感測電極和可調式軟帽。我們用提出的系統比較使用乾式電極和傳統濕式電極量測腦電波的效能。得到了乾式電極和濕式電極之間信號的高相關度，以保證其信號品質。此外，四個腦電信號的差異特徵（即正常，眨眼，閉眼和牙齒緊咬信號）由16個乾式電極量測，以確保他們是潛在並能被量測的，可以在現實生活中的認知神經科學的應用。另一方面，結合加速度計和陀螺儀與基於EEG的BCI系統。我們得到了介面顯示結果和實際移動之間的高一致性，提供頭部運動和傾斜監測。這個BCI系統有可能發展成優秀的可移動式腦成像系統或空間認知導航系統，並協助人類行為的研究。這項研究提供了一種新的見解，在認知神經科學領域，表明在現實生活中的腦功能研究的可能性。

Understanding brain function via the electroencephalography (EEG) method is an important issue for cerebral nervous system. Many brain-computer interface (BCI) systems are reliable to study those diseases, but their bulky size and the use of wet sensors make them uncomfortable and inconvenient for users. To overcome the limitations of conventional BCI systems, a wireless and wearable multi-channel EEG-based BCI system is proposed in this study. This system includes a wireless data acquisition device, dry spring-loaded sensors and a size-adjustable soft cap. We have compared performance of the proposed system with dry versus conventional wet sensors. A significant positive correlation between wet and dry sensors was achieved, thus guaranteeing the performance of this system. Moreover, four different features of EEG signals (i.e., normal, blink, closed eyes and teeth-clamping signals) were measured by 16 dry sensors to ensure they had the potential to be performed in real-life cognitive neuroscience applications. On the other hand, we combine the accelerometer and gyroscope into the EEG-based BCI system. The significant correlation between display result and actually moving was achieved to providing monitoring of head movement and inclination. It has the possibility to develop into excellent mobile brain imaging system or spatial cognitive navigation system, and assist human behavior research. This study presents novel insights into the cognitive neuroscience field, showing the possibility of studying brain functions under real-life conditions.