Title :
Event-driven data and power management in high-density neural recording microsystems
Author :
Gosselin, Benoit ; Sawan, Mohamad
Author_Institution :
Dept. of Electr. Eng., Ecole Polytech. de Montreal, Montreal, QC, Canada
fDate :
June 28 2009-July 1 2009
Abstract :
We present design approaches and circuit techniques to perform data and power management in high-density neural recording implants. The proposed strategies employs low-power automatic detectors and dedicated neural signal processing circuits to take advantage on the discontinuous nature of neural signals presenting low duty cycles. We show that the suggested approaches enable for significant data and power reductions compared with standard design practices. Also, design methods to optimize low-power analog circuits are discussed.
Keywords :
analogue circuits; bioMEMS; bioelectric potentials; data reduction; medical signal processing; neurophysiology; optimisation; prosthetics; dedicated neural signal processing circuits; event-driven data; high-density neural recording microsystems; implants; low-power analog circuits; low-power automatic detectors; optimization; power management; Analog circuits; Clocks; Detectors; Energy consumption; Energy management; Engineering management; Event detection; Implants; Power system management; Transceivers; Data reduction; High-density sensors; Low-power biomedical electronics; Neural recording; Power management;
Conference_Titel :
Circuits and Systems and TAISA Conference, 2009. NEWCAS-TAISA '09. Joint IEEE North-East Workshop on
Conference_Location :
Toulouse
Print_ISBN :
978-1-4244-4573-8
Electronic_ISBN :
978-1-4244-4574-5
DOI :
10.1109/NEWCAS.2009.5290509