DocumentCode :
2549129
Title :
A low power merge cell processor for real-time spike sorting in implantable neural prostheses
Author :
Linderman, Michael D. ; Meng, Teresa H.
Author_Institution :
Stanford Univ., CA
fYear :
2006
fDate :
21-24 May 2006
Lastpage :
4109
Abstract :
Extremely low power consumption is the critical constraint for designing implantable neural decoders that interface directly with the nervous system. Typically a system with such strict constraints is implemented as an ASIC; however, the rapid progress in the field mandates a more flexible solution. In this paper we introduce a new general architecture, the Merge Framework, and its low power implementation for real-time spike sorting in cortical control applications, that offers a flexible and powerful programming model with near ASIC power efficiency
Keywords :
low-power electronics; program processors; prosthetics; sorting; ASIC power efficiency; cortical control applications; flexible programming model; implantable neural decoders; implantable neural prostheses; low power consumption; low power merge cell processor; nervous system; powerful programming model; real-time spike sorting; Application specific integrated circuits; Bandwidth; Informatics; Merging; Pattern recognition; Personal communication networks; Power system modeling; Prosthetics; Sorting; Timing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
Conference_Location :
Island of Kos
Print_ISBN :
0-7803-9389-9
Type :
conf
DOI :
10.1109/ISCAS.2006.1693532
Filename :
1693532
Link To Document :
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