Title :
A micro-power neural spike detector and feature extractor in .13μm CMOS
Author :
Holleman, Jeremy ; Mishra, Apurva ; Diorio, Chris ; Otis, Brian
Author_Institution :
Dept. of Electr. Eng., Univ. of Washington, Seattle, WA
Abstract :
We present a fully-integrated system for the detection and characterization of action potentials observed in extracellular neural recordings. The circuit includes an analog implementation of the nonlinear energy operator for spike detection. The minimum and maximum value of detected spikes are captured by peak detectors and digitized by an on-chip successive approximation ADC to provide a compact description of the spike waveform. The circuit is implemented in a .13 mum CMOS process. It occupies .17 mm2 of chip area and consumes 1 muW from a 1 V supply.
Keywords :
CMOS analogue integrated circuits; analogue-digital conversion; peak detectors; ADC; extracellular neural recordings; feature extractor; micropower neural spike detector; nonlinear energy operator; onchip successive approximation; size 0.13 mum; Analog-digital conversion; CMOS process; Computer vision; Counting circuits; Delay; Detectors; Extracellular; Feature extraction; Timing; Virtual manufacturing;
Conference_Titel :
Custom Integrated Circuits Conference, 2008. CICC 2008. IEEE
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-2018-6
Electronic_ISBN :
978-1-4244-2019-3
DOI :
10.1109/CICC.2008.4672089