Title :
An Energy-Efficient Biomedical Signal Processing Platform
Author :
Kwong, Joyce ; Chandrakasan, Anantha P.
Author_Institution :
Texas Instrum., Inc., Dallas, TX, USA
fDate :
7/1/2011 12:00:00 AM
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 0.5 V-1.0 V 16-bit 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 :
SRAM chips; biomedical electronics; body sensor networks; electrocardiography; electroencephalography; medical signal processing; microcontrollers; optimisation; patient monitoring; 16-bit microcontroller; CPU; EEG; SRAM; ambulatory medical monitoring; biological signals; block-level power gating; electrocardiography; energy-efficient biomedical signal processing platform; optimization; programmable accelerators; voltage 0.5 V to 1 V; voltage scaling; wearable sensor nodes; Algorithm design and analysis; Clocks; Computer architecture; Hardware; Signal processing algorithms; Switches; Accelerators; biomedical signal processing; low-voltage;
Journal_Title :
Solid-State Circuits, IEEE Journal of
DOI :
10.1109/JSSC.2011.2144450
