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A Mixer-First Analog Front-End for Dry-Electrode Bioimpedance Spectroscopy
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0001-7549-0858
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0003-3802-7834
2023 (English)In: BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a high input impedance, low-noise, and low-distortion analog front-end (AFE) for bioimpedance (bio-Z) spectroscopy measurements targeting neuromuscular health assessments. The proposed 8-phase quadrature mixer-first architecture achieves a high input impedance through passive mixers driven by non-overlapping clocks. The 8-phase signals are recombined to extract the real and imaginary parts of the bio-Z, while rejecting unwanted harmonics to improve linearity. Programmability of the AFE enables accurate bio-Z measurements up to 10 kΩ for 11 logarithmically spaced frequencies, in the 1 kHz to 1 MHz frequency range. The AFE, designed in a 0.18 μm CMOS process, consumes 245.99 μW at the lowest gain and 300.56 μW at the highest gain, and occupies 2.4 mm2 silicon area. Post-layout simulation results show that the input impedance is always higher than the electrode impedance by more than 10x. The AFE achieves a sensitivity of 7.7 mΩrms, and a maximum SNDR of 103.87 dBFS over a 61 Hz bandwidth. These results demonstrate that the proposed AFE enables bio-Z measurements, using dry electrodes, with errors below 1%.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023.
Keywords [en]
analog front-end, bioimpedance spectroscopy, dry electrodes, high input impedance, low-distortion, low-noise, passive mixer, programmable gain
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343702DOI: 10.1109/BioCAS58349.2023.10388966Scopus ID: 2-s2.0-85184898068OAI: oai:DiVA.org:kth-343702DiVA, id: diva2:1839897
Conference
2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023, Toronto, Canada, Oct 19 2023 - Oct 21 2023
Note

QC 20240223

Part of ISBN 979-8-3503-0026-0

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-23Bibliographically approved

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Fernández Schrunder, AlejandroRusu, Ana

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