DocumentCode :
75805
Title :
Compressed Sensing Analog Front-End for Bio-Sensor Applications
Author :
Gangopadhyay, Daibashish ; Allstot, Emily G ; Dixon, Anna M R ; Natarajan, Kamali ; Gupta, Swastik ; Allstot, David J.
Author_Institution :
Marvell Semicond., Santa Clara, CA, USA
Volume :
49
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
426
Lastpage :
438
Abstract :
In a conventional bio-sensor, key signal features are acquired using Nyquist-rate analog-to-digital conversion without exploiting the typical bio-signal characteristic of sparsity in some domain (e.g., time, frequency, etc.). Compressed sensing (CS) is a signal processing paradigm that exploits this sparsity for commensurate power savings by enabling alias-free sub-Nyquist acquisition. In a severely energy constrained sensor, CS also eliminates the need for digital signal processing (DSP). A fully-integrated low-power CS analog front-end (CS-AFE) is described for an electrocardiogram (ECG) sensor. Switched-capacitor circuits are used to achieve high accuracy and low power. Implemented in 0.13 μm CMOS in 2×3 mm2, the prototype comprises a 384-bit Fibonacci-Galois hybrid linear feedback shift register and 64 digitally-selectable CS channels with a 6-bit C-2C MDAC/integrator and a 10-bit C-2C SAR ADC in each. Clocked at 2 kHz, the total power dissipation is 28 nW and 1.8 μW for one and 64 active channels, respectively. CS-AFE enables compressive sampling of bio-signals that are sparse in an arbitrary domain.
Keywords :
CMOS integrated circuits; analogue-digital conversion; biomedical electronics; biosensors; circuit feedback; compressed sensing; electrocardiography; feature extraction; integrating circuits; low-power electronics; medical signal processing; shift registers; switched capacitor networks; wireless sensor networks; 10-bit C-2C SAR ADC; 6-bit C-2C MDAC-integrator; CMOS; ECG; Fibonacci-Galois hybrid linear feedback shift register; Nyquist-rate analog-to-digital conversion; alias-free subNyquist acquisition; arbitrary domain; biosignal characteristics; commensurate power savings; compressive sampling; conventional biosensor applications; digital signal processing; digitally-selectable compressed sensing channels; electrocardiogram sensor; frequency 2 kHz; fully-integrated low-power compressed sensing analog front-end; key signal features; power 1.8 muW; power 28 nW; power dissipation; prototype; severely energy constrained sensor; signal processing paradigm; sparsity; switched-capacitor circuits; Accuracy; Compressed sensing; Electrocardiography; Noise; Receivers; Sparse matrices; Vectors; Analog-to-digital converters; ECG; SAR ADC; analog-to-information converters; biomedical sensors; body-area networks; compressed sensing; compressive sampling; multiplying DAC; sub-Nyquist sampling; wavelets; wireless sensors;
fLanguage :
English
Journal_Title :
Solid-State Circuits, IEEE Journal of
Publisher :
ieee
ISSN :
0018-9200
Type :
jour
DOI :
10.1109/JSSC.2013.2284673
Filename :
6722935
Link To Document :
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