A 950 nW Analog-Based Data Reduction Chip for Wearable EEG Systems in Epilepsy

Abstract

Long-term EEG monitoring is an important tool used for the diagnosis of epilepsy. Truly Wearable EEG can be considered as the future of ambulatory EEG units, which are the current standard for long-term EEG monitoring. Replacing these short lifetime, bulky units with long-lasting miniature and wearable devices which can easily be worn by patients will result in more EEG data being acquired for longer monitoring periods. This paper presents an analog based data reduction integrated circuit that would reduce the amount of power required to transmit EEG data by identifying the sections of data that are interesting for diagnostic purposes while discarding background activity. Using the data reduction system as part of a miniature wireless EEG monitoring unit would yield significant reductions in power consumption since the transmitter will only be switched on based on the data reduction system output.A system prototype chip has been fabricated in a 0.35 µm CMOS process. The system consumes 760 nA from a 1.25 V supply and is able to achieve a sensitivity of 87% while transmitting 45% of the overall EEG data.

Realization of Analog Wavelet Filter Using Hybrid Genetic Algorithm for On-Line Epileptic Event Detection

“…. , n) in (6) are determined values calculated by Maclaurin series expansion shown as (7). And so, the stability of approximated transfer function depends strongly upon the inter-relationship between wavelet scale, time delay and filter order.…”

“…. ., 7) are searched within the bounds of (0,10), initial population size is 100, selection operator is tournament, crossover and mutation operators are arithmetic with probability of 0.8 and adaptive method, respectively.…”

“…However, long-term monitoring can generate huge amounts of EEG data, and make wireless transmission very powerhungry, that is unsuitable for the battery powered WAEEG which has stringent power budget. As a solution to the aforementioned problem, online data reduction for WAEEG system has been presented, in which epileptic event detection algorithm (EEDA) is used to reduce the amount of wirelessly transmitted EEG data, and thus the power dissipation [7], [8]. Fig.…”

Analog Continuous-Time Filter Designing for Morlet Wavelet Transform Using Constrained L2-Norm Approximation

“…And the chip with total area occupancy of 0.008mm 2 is achieved. In [13], a 950nW analog-based data reduction chip is proposed. And the low power consumption makes it more suitable for the application in wearable Electroencephalograph (EEG).…”

“…Taking these issues into account, in this paper, the continuous wavelet transform is implemented in an integrated low-power Gm-C filter, which is well suited for the application in wearable devices. Actually, the conception of integrated analog implementation of the continuous wavelet transform for the application in wearable devices has been studied by some previous works, such as [13], [21], [20]. However, in this paper, we pay more attention to the accuracy of the analog implementation of the wavelet transform.…”