DocumentCode :
55325
Title :
A Fully-Asynchronous Low-Power Implantable Seizure Detector for Self-Triggering Treatment
Author :
Mirzaei, Mohammad ; Salam, M. Tariqus ; Nguyen, D.K. ; Sawan, Mohamad
Author_Institution :
Dept. of Electr. Eng., Polytech. Montreal, Montreal, QC, Canada
Volume :
7
Issue :
5
fYear :
2013
fDate :
Oct. 2013
Firstpage :
563
Lastpage :
572
Abstract :
In this paper, we present a new asynchronous seizure detector that is part of an implantable integrated device intended to identify electrographic seizure onset and trigger a focal treatment to block the seizure progression. The proposed system has a low-power front-end bioamplifier and a seizure detector with intelligent mechanism to reduce power dissipation. This system eliminates the unnecessary clock gating during normal neural activity monitoring mode and reduces power dissipation in the seizure detector; as a result, this device is suitable for long-term implantable applications. The proposed system includes analog and digital building blocks with programmable parameters for extracting electrographic seizure onset information from real-time EEG recordings. Sensitivity of the detector is enhanced by optimizing the variable parameters based on specific electrographic seizure onset activities of each patient. The detection algorithm was validated using Matlab tools and implemented in standard 0.13 μm CMOS process with total die area of 1.5×1.5 mm2. The fabricated chip is validated offline using intracranial EEG recordings from two patients with refractory epilepsy. Total power consumption of the chip is 9 μW and average detection delay is 13.7 s after seizure onset, well before the onset of clinical manifestation. The proposed system achieves an accurate detection performance with 100% sensitivity and no false alarms during the analyses of 15 seizures and 19 non-seizure datasets.
Keywords :
amplifiers; biomedical equipment; electroencephalography; low-power electronics; medical disorders; medical signal detection; medical signal processing; neurophysiology; patient treatment; power consumption; prosthetics; Matlab tools; analog digital building blocks; average detection delay; clock gating; detection algorithm; detection performance; electrographic seizure onset; electrographic seizure onset information; full-asynchronous low-power implantable seizure detector; implantable integrated device; intelligent mechanism; intracranial EEG recordings; low-power front-end bioamplifier; nonseizure datasets; normal neural activity monitoring mode; power 9 W; power dissipation; programmable parameters; real-time EEG recordings; refractory epilepsy; seizure progression; self-triggering treatment; size 0.13 mum; standard CMOS process; time 13.7 s; total die area; total power consumption; Detectors; Epilepsy; Medical treatment; Noise; Power dissipation; Time-frequency analysis; Variable speed drives; Asynchronous; implantable device; seizure detector; Algorithms; Electroencephalography; Equipment Design; Equipment Failure Analysis; Humans; Monitoring, Physiologic; Prostheses and Implants; Seizures; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Biomedical Circuits and Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1932-4545
Type :
jour
DOI :
10.1109/TBCAS.2013.2283502
Filename :
6634266
Link To Document :
بازگشت