A 65nm CMOS lossless bio-signal compression circuit with 250 femtoJoule performance per bit.

Clicks: 273
ID: 41929
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #9 of 10 articles by views in ieee transactions on biomedical circuits and systems

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
A 65nm CMOS integrated circuit implementation of a bio-physiological signal compression device is presented, reporting exceptionally low power, and extremely low silicon area cost, relative to state-of-the-art. A novel 'xor-log2-sub-band' data compression scheme is evaluated, achieving modest compression, but with very low resource cost. With the intent to design the 'simplest useful compression algorithm', the outcome is demonstrated to be very favourable where power must be saved by trading off compression effort against data storage capacity, or data transmission power, even where more complex algorithms can deliver higher compression ratios. A VLSI design and fabricated Integrated Circuit implementation are presented, and estimated performance gains and efficiency measures for various bio-medical use-cases are given. Power costs as low as 1.2 pJ per sample-bit are suggested for a 10kSa/s data-rate, whilst utilizing a power-gating scenario, and dropping to 250fJ/bit at continuous conversion data-rates of 5MSa/sec. This is achieved with a diminutive circuit area of 155 [Formula: see text]. Both power and area appear to be state-of-the-art in terms of compression versus resource cost, and this yields benefit for system optimization.
Reference Key
bailey2019aieee Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bailey, Chris;Dai, Chengliang;Austin, Jim;
Journal ieee transactions on biomedical circuits and systems
Year 2019
DOI
10.1109/TBCAS.2019.2938672
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.