An Ultra-Low Power RSSI Amplifier for EEG Feature Extraction to Detect Seizures

被引:5
|
作者
Zhang, Yuqing [1 ]
Mirchandani, Nikita [1 ]
Abdelfattah, Safaa [1 ]
Onabajo, Marvin [1 ]
Shrivastava, Aatmesh [1 ]
机构
[1] Northeastern Univ, Dept Elect & Comp Engn, Boston, MA 02115 USA
基金
美国国家科学基金会;
关键词
Machine learning; analog computing; EEG-based seizure detection; support-vector machine; received signal strength indicator (RSSI); switched capacitor circuit;
D O I
10.1109/TCSII.2021.3099056
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This brief presents an ultra-low power received signal strength indicator (RSSI) amplifier circuit that can be used to detect seizures through feature extraction from electroen-cephalography (EEG) signals. The RSSI-based feature extraction method provides a low-power area-efficient solution for analog computing based seizure detection hardware. A 6-stage RSSI amplifier circuit was designed in 65nm CMOS technology to cover the dynamic range of EEG signals with an area of 266 mu m x 531 mu m. Measurement results of the RSSI circuit show that it has a power consumption of 31.6nW, covers a 45dB dynamic range, and has a linearity error of less than +/- 1dB.
引用
收藏
页码:329 / 333
页数:5
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