DocumentCode
3608694
Title
A 16-Channel Patient-Specific Seizure Onset and Termination Detection SoC With Impedance-Adaptive Transcranial Electrical Stimulator
Author
Awais Bin Altaf, Muhammad ; Chen Zhang ; Yoo, Jerald
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Masdar Inst. of Sci. & Technol., Abu Dhabi, United Arab Emirates
Volume
50
Issue
11
fYear
2015
Firstpage
2728
Lastpage
2740
Abstract
A 16-channel noninvasive closed-loop beginning-and end-of-seizure detection SoC is presented. The dual-channel charge recycled (DCCR) analog front end (AFE) achieves chopping and time-multiplexing an amplifier between two channels simultaneously which exploits fast-settling DC servo-loop with current consumption and NEF of 0.9 μA/channel and 3.29/channel, respectively. The dual-detector architecture (D2A) classification processor utilizes two linear support-vector machine (LSVM) classifiers based on digital hysteresis to enhance both the sensitivity and the specificity simultaneously. The pulsating voltage transcranial electrical stimulator (PVTES) automatically configures the number of pulses to control the amount of charge delivered based on skin-electrode impedance variation in efforts to suppress the seizure activity, while burning only 2.45 μW. The 25 mm2 SoC implemented in 0.18 μm CMOS consumes 2.73 μJ/classification for 16 channels with an average sensitivity, specificity, and latency of 95.7%, 98%, and 1 s, respectively.
Keywords
bioelectric phenomena; biomedical electrodes; electroencephalography; hysteresis; medical disorders; medical signal detection; neurophysiology; patient treatment; signal classification; support vector machines; system-on-chip; 16-channel noninvasive closed-loop beginning-and end-of-seizure detection; 16-channel patient-specific seizure onset; AFE; CMOS; D2A; DCCR; LSVM; NEF; PVTES; SoC; amplifier; chopping; current consumption; digital hysteresis; dual-channel charge recycled analog front end; dual-detector architecture classification processor; fast-settling DC servo-loop; impedance-adaptive transcranial electrical stimulator; linear support-vector machine classifier; power 2.45 muW; pulsating voltage transcranial electrical stimulator; seizure activity; skin-electrode impedance variation; termination detection; time 1 s; time-multiplexing; Choppers (circuits); DSL; Electroencephalography; Impedance; Iron; Switches; System-on-chip; Analog sleep mode; charge recycling; continuous health monitoring; digital hysteresis; electroencephalogram (EEG); epilepsy; machine learning; noninvasive; seizure detection; support vector machine (SVM); system-on-chip (SoC); transcranial electrical stimulation;
fLanguage
English
Journal_Title
Solid-State Circuits, IEEE Journal of
Publisher
ieee
ISSN
0018-9200
Type
jour
DOI
10.1109/JSSC.2015.2482498
Filename
7302516
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