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An 8-channel scalable EEG acquisition SoC with fully integrated patient-specific seizure classification and recording processor

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Authors

Yoo, Jerald; Yan, Long; El-Damak, Dina; Altaf, Muhammad Bin; Shoeb, Ali; Yoo, Hoi-Jun; Chandrakasan, Anantha

Issue Date
2012
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
Digest of Technical Papers - IEEE International Solid-State Circuits Conference, Vol.55, pp.292-293
Abstract
Tracking seizure activity to determine proper medication requires a small form factor, ultra-low power sensor with continuous EEG classification. Technical challenges arise from: 1) patient-to-patient variation of seizure pattern on EEG, 2) fully integrating an ultra-low power variable dynamic range instrumentation circuits with seizure detection processor, and 3) reducing communication overhead. Reference [1] extracted EEG features locally on-chip to reduce the data being transmitted, and saved power by 1/14 when compared to raw EEG data transmission. However, it still needs data transmission and off-chip classification to detect and to store seizure activity. This paper presents an ultra-low power scalable EEG acquisition SoC for continuous seizure detection and recording with fully integrated patient-specific Support Vector Machine (SVM)-based classification processor. © 2012 IEEE.
ISSN
0193-6530
URI
https://hdl.handle.net/10371/200845
DOI
https://doi.org/10.1109/ISSCC.2012.6177019
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부교수
  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area Biomedical Applications, Energy-Efficient Integrated Circuits

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