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72195 |
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|a dc
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|a Kwong, Joyce
|e author
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Chandrakasan, Anantha P.
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|a Kwong, Joyce
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|a Chandrakasan, Anantha P.
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|a Chandrakasan, Anantha P.
|e author
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|a An Energy-Efficient Biomedical Signal Processing Platform
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|b Institute of Electrical and Electronics Engineers (IEEE),
|c 2012-08-17T18:46:55Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/72195
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|a This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5V-1.0V 16b microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applications of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal processing tasks at 133 to 215× lower energy than the general-purpose CPU. When running complete EEG and EKG applications using both CPU and accelerators, the platform achieves 10.2× and 11.5× energy reduction respectively compared to CPU-only implementations.
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|a Natural Sciences and Engineering Research Council of Canada (NSERC). Fellowship
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|a en_US
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|a Article
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|t 2010 Proceedings of the ESSCIRC
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