創新穿戴式超低功耗無線微型腦波量測系統之設計與驗證

Abstract

腦機介面技術是一種溝通介於大腦與外在世界的工具。然而為了收錄高品質的腦波，所使用的標準化量測儀器往往笨重而巨大，也造成日常生活中收錄腦波並實際應用成為一項艱難的任務。為了改善這項狀況，雖然也有許多可攜式腦波量測系統已經被提出，它們仍然在日常生活中使用上不足夠地方便。因此我們提出一套穿戴式微型無線腦波量測系統，期望此系統能夠使腦波技術在日常生活中的具有更高的可應用性。 本系統包括兩個部分: 一、穿戴式超低功耗無線微型腦波量測系統，二、Android端腦波展示程式。本系統可使用傳統濕電極、貼片電極，亦可以使用新式乾式頂針電極。腦波資料將以無線傳輸至使用者介面並紀錄並儲存在手機端以在離線分析，而在認知實驗中常需要的事件傳輸則以RS232與USB OTG 整合來進行事件紀錄。 本系統亦致力於超低耗能的設計，並且必須維持訊號品質的優越。另一方面，本系統為了符合多通道腦波應用，亦有系統通道同步設計；本系統亦設計前端腦波能量頻譜分析技術，亦可提高更多的腦波應用性。最後，本系統亦經過多項驗證實驗的測試。相當適合於生活中腦波應用包括睡眠品質監測、專注力量測、腦機介面系統中使用。是故，本系統的微型化、低功率化、功能性化亦是腦機介面的應用進入生活中消費性電子領域的一個重要里程碑。

The brain-computer interface (BCI) technique is a method that provides a direct communication pathway between the brain and the external worlds. However, the instruments with high measured signal quality are always heavy and huge. Thus, recording EEG trends to be a difficult task in daily life. Although there were some portable EEG systems designed for improving this situation, they aren’t enough for daily life conveniently. Therefore, we mention a wearable wireless micro EEG acquisition system. We expect to improve the availability of BCI technique used in daily life. This system includes two parts: (1) Wearable ultra-low power wireless micro EEG acquisition system, (2) User-interface for EEG display based on Android 4.3 system. This system can be used with wet sensor, Ag/AgCl electrode or dry sensors. Then the user-interface receives EEG data via wireless communication and also saves raw data as a file for off-line analysis. On the other hand, RS232 and USB on-the-go would be used for sending event’s tag in some cognitive experiments. Although this system is designed with low-power techniques completely, it also maintains the signal quality. The systems’ synchronization is designed for some EEG applications with multi-channels. In addition, this system can achieve front-end EEG power-spectrum analysis for more BCI practicalities. Finally, we also verify the performance of our low-energy EEG system by means of many verification experiments. The results show that our system has high reliability of EEG processing and recording. It's suitable for some applications such as detection of sleep quality, attention, brain-control interface, etc. Therefore, the system’s pros of micro-sized, low-power consumption and functionalizing would promote applications of BCI technique for consumer electronics market.