An ultra-low power system-on-chip for automatic sleep staging

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Title: An ultra-low power system-on-chip for automatic sleep staging
Authors: Imtiaz, SA
Jiang, Z
Rodriguez Villegas, E
Item Type: Journal Article
Abstract: This paper presents an ultra-low power SoC for automatic sle ep staging using a single electroen- cephalography (EEG) channel. The system integrates an anal og front-end for EEG data acquisition and a digital processor to extract spectral features from this da ta and classify them into one of the sleep stages. The digital processor consists of multiple blocks implemen ting an automatic sleep staging algorithm that uses a set of contextual decision trees controlled by a s tate machine. The processor is designed to stay in idle mode at most times waking up only when computat ions are required. In addition, the mathematical operations are implemented in a way such that t he number of datapath components needed is very small. The SoC is implemented in AMS 0.18 μ m CMOS technology and is powered using a single 1.25V supply. Its power consumption is measured to be 575 μ W while its classification accuracy using real EEG data is 98.7%.
Issue Date: 25-Jan-2017
Date of Acceptance: 30-Dec-2016
ISSN: 1558-173X
Start Page: 822
End Page: 833
Journal / Book Title: IEEE Journal of Solid State Circuits
Volume: 52
Issue: 3
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: Contract No. 239749
Keywords: Science & Technology
Engineering, Electrical & Electronic
Electroencephalogram (EEG)
low-power biomedical system
sleep classification algorithm
sleep staging
Electrical & Electronic Engineering
0906 Electrical And Electronic Engineering
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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