An Energy-Efficient Biomedical Signal Processing Platform

Author

Kwong, Joyce ; Chandrakasan, Anantha P.

Author_Institution

Texas Instrum., Inc., Dallas, TX, USA

Volume

46

Issue

7

fYear

2011

fDate

7/1/2011 12:00:00 AM

Firstpage

1742

Lastpage

1753

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;

fLanguage

English

Journal_Title

Solid-State Circuits, IEEE Journal of

Publisher

ieee

ISSN

0018-9200

Type

jour

DOI

10.1109/JSSC.2011.2144450

Filename

5783951