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This paper describes a full system-on-chip to automatically detect sleep spindle events from scalp EEG signals. These events, which are known to play an important role on memory consolidation during sleep, are also characteristic of a number of neurological diseases. The operation of the system is based on a previously reported algorithm which used the Teager Energy Operator (TEO), together with the Spectral Edge Frequency (SEF50) achieving over 70% sensitivity and 98% specificity. The algorithm is now converted into a hardware analog based customized implementation in order to achieve extremely low levels of power. Experimental results prove that the system, which is fabricated in a 0.18 µm technology, is able to operate from a 1.25 V power supply consuming only 515 nW, with an accuracy which is comparable to its software counterpart.