An Energy-Efficient Biomedical Signal Processing Platform

Author(s)
Kwong, Joyce; Chandrakasan, Anantha P.
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Abstract
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.
Date issued
2010-09
URI
http://hdl.handle.net/1721.1/72195
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
2010 Proceedings of the ESSCIRC
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kwong, Joyce, and Anantha P. Chandrakasan. “An Energy-efficient Biomedical Signal Processing Platform.” 2010 Proceedings of the ESSCIRC, 2010. 526–529.
Version: Final published version
ISBN
978-1-4244-6662-7
ISSN
1930-8833
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