Title :
An energy-efficient biomedical signal processing platform
Author :
Kwong, Joyce ; Chandrakasan, Anantha P.
Author_Institution :
Massachusetts Inst. of Technol., Cambridge, MA, USA
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.
Keywords :
electrocardiography; electroencephalography; medical signal processing; microcontrollers; optimisation; power aware computing; sensors; EEG; EKG; SRAM; block level power gating; energy efficient biomedical signal processing; microcontroller; optimization; voltage scaling; wearable sensor nodes; Accuracy; Clocks; Computer architecture; Finite impulse response filter; Hardware; Random access memory; Switches;
Conference_Titel :
ESSCIRC, 2010 Proceedings of the
Conference_Location :
Seville
Print_ISBN :
978-1-4244-6662-7
DOI :
10.1109/ESSCIRC.2010.5619759
