英譯漢：

神經(jīng)信號處理系統(tǒng)

neural signal analysis system

　　Brain-machine interfaces are promising tools for rehabilitation medicine and medical electronics. Most conventional neural signal analysis systems used in brain-computer interfaces are composed of silicon CMOS circuits. However, with the increasing number of recording electrodes, the systems face great challenges in terms of power consumption and delays.

　　Researchers from Tsinghua University have developed a memristor-based neural signal analysis system and used the system to implement the filtering and identification of epilepsy-related neural signals, achieving an accuracy of 93.46 percent. The power consumption of the system is less than one four-hundredth of that of conventional neural signal analysis systems.

　　腦機接口技術(shù)在康復(fù)醫(yī)學(xué)、醫(yī)療電子等領(lǐng)域有著光明的發(fā)展前景。目前，主流的腦機接口中的神經(jīng)信號分析模塊由硅CMOS電路構(gòu)成，但隨著腦機接口中的信號采集通道數(shù)的增加，系統(tǒng)面臨著功耗和延時等方面的巨大挑戰(zhàn)。

　　清華大學(xué)研究團隊研制出了基于憶阻器陣列的腦電神經(jīng)信號處理系統(tǒng)，對大腦癲癇神經(jīng)信號進行過濾與識別，實現(xiàn)了93.46%的高準(zhǔn)確率。與傳統(tǒng)神經(jīng)信號處理系統(tǒng)相比，該系統(tǒng)將功耗降低了400多倍。

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