Epilepsy is one of the most common serious brain
disorders affecting 1% of the world population. Epileptic seizure
events are caused by abnormal excessive neuronal activity in the
brain, which may be associated with behavioural changes that
severely affect the patients’ quality of life. These events are manifested as abnormal activity in electroencephalography (EEG)
recordings of individuals with epilepsy. This paper presents the
on-chip implementation of an algorithm that, operating on the
principle of data selection applied to seizures, would be able to
reduce the power consumption of EEG devices, and consequently
their size, thereby significantly increasing their usability. In order
to reduce the power consumed by the on-chip implementation of
the algorithm, mathematical approximations have been carried
out to allow for an analog implementation, resulting in the power
consumed by the system to be negligible in comparison to other
blocks in an EEG device. The system has been fabricated in a
0.18 µm CMOS process, consumes 1.14 µW from a 1.25 V supply
and achieves a sensitivity of 98.5% while only selecting 52.5%
of the EEG data for transmission.