對於改善大腦受傷或者神經異常的病人而言，腦機介面(Brain-Machine- Interface, BMI)的研究越來越受到矚目，其中最主要的原因，是BMI在高時空解析度下具有可靠刺激與紀錄多個神經細胞活動的能力，而這對神經科學進展來說，也是非常重要的。

在這篇論文中，我們提出了一個整合多通道紀錄與刺激的腦機介面，並透過電腦或Android系統來與神經細胞做溝通，藉此改善大腦受損或神經異常的病人恢復他們的生理機能。此外，我們以無線傳輸的方式來傳送資料與電源，讓使用者的行動不會受到傳輸線的限制，以增加腦機介面在使用上的便利性。

而在本篇論文所提出的腦機介面當中，Information Hub扮演著相當重要的腳色。Information Hub根據外部輸入的指令，調整系統的記錄與刺激等各項參數，並產生紀錄與刺激電路所需要的控制訊號來控制個電路的運作。此外，Information Hub亦將記錄到的神經資料作處理，以符合無線傳輸的需求。並進一步對資料做壓縮來節省無線傳輸時的功率消耗，藉由改良過的Lemp-Ziv壓縮法，達到1.8以上的壓縮率，並節省了50%左右的無線傳輸功耗。

藉由混和訊號SoC的設計流程，並透過TSMC18 1P6M製程，將此腦機介面實作出兩個版本。在第一個版本的晶片當中，晶片面積為3.3 x 2.4 mm2，而Information Hub佔了1.7 x 1 mm2的面積，並且在2 MHz的操作頻率下，有486μW的功率消耗。而在第二版本的晶片當中，進一步改良了硬體消耗，其面積大約為3.06 x 2.53 mm2，而Information Hub佔了2.6 x 0.5 mm2的面積，並且在2 MHz的操作頻率下消耗469μW的功率。

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