Paper Info
Title
Direct Digital Wavelet Synthesis for Embedded Biomedical Microsystems
Abstract
This paper presents a compact direct digital wavelet synthesizer for extracting phase and amplitude data from cortical recordings using a feed-forward recurrent digital oscillator. These measurements are essential for accurately decoding local-field - potentials in selected frequency bands. Current systems extensively to rely large digital cores to efficiently perform Fourier or wavelet transforms which is not viable for many implants. The proposed system dynamically controls oscillation to generate frequency selective quadrature wavelets instead of using memory intensive sinusoid/cordic look-up-tables while retaining robust digital operation. A MachXO3LF Lattice FPGA is used to present the results for a 16 bit implementation. This configuration requires 401 registers combined with 283 logic elements and also accommodates real-time reconfigurability to allow ultra-low-power sensors to perform spectroscopy with high-fidelity.
Year
DOI
Venue
2018
10.1109/BIOCAS.2018.8584787
2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Keywords
Field
DocType
direct digital wavelet synthesis,embedded biomedical microsystems,compact direct digital wavelet synthesizer,amplitude data,cortical recordings,feed-forward recurrent digital oscillator,selected frequency bands,digital cores,wavelet transforms,frequency selective quadrature wavelets,robust digital operation,MachXO3LF Lattice FPGA,memory intensive sinusoid-cordic look-up-tables
Reconfigurability,Computer science,16-bit,Field-programmable gate array,Electronic engineering,Modulation,CORDIC,Time–frequency analysis,Wavelet transform,Wavelet
Conference
ISSN
ISBN
Citations 
2163-4025
978-1-5386-3604-6
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Lieuwe B. Leene184.69
Timothy G. Constandinou27838.42