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Fast capacitance-to-digital converter with internal reference

Lookup NU author(s): Kaiyuan Gao, Dr Delong Shang, Dr Fei Xia, Professor Alex Yakovlev

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE, 2016.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

Conventional capacitance-to-digital converters (CDC) widely used in IoTs particularly in portable applications tend to make use of complex analog-to-digital technologies. However this can be power hungry and take long conversion time. In addition, the analog parts are hard to implement in ASICs, especially under wide working conditions, such as energy harvesting scenarios. Recently digitalized CDCs were proposed to meet these challenges, but existing solutions still required long conversion time, and need external voltage references limiting their portability. A novel CDC with low energy consumption and short measuring time is presented in this paper. With a new internal time reference method, it is fully portable and achieves fast conversion response. A method of decoupling the sensing resolution from the discharge mechanism enhances the programmability of such sensors making energy to precision tradeoffs straightforward. This paper contains both theoretical analysis and the experimental demonstration of these methods. This new solution can reduce the conversion time by more than 20 times, and reduce energy consumption by half.


Publication metadata

Author(s): Gao K, Shang D, Xia F, Yakovlev A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: IEEE Biomedical Circuits and Systems Conference (BioCAS)

Year of Conference: 2016

Pages: 264-267

Online publication date: 26/01/2017

Acceptance date: 17/10/2016

Date deposited: 22/02/2017

Publisher: IEEE

URL: http://dx.doi.org/10.1109/BioCAS.2016.7833782

DOI: 10.1109/BioCAS.2016.7833782

Library holdings: Search Newcastle University Library for this item

ISBN: 9781509029594


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