Title | ||
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A 10 <tex>$\mu \mathrm{W}-74.6\mathrm{dB}$</tex> THD Arterial Pulse Waveform Sensing System with Automatic Bridge-Offset Calibration and Super Class-AB Output Stage |
Abstract | ||
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This paper presents a power-efficient, highly-linear sensing system for arterial pulse waveform (APW) acquisition. The system consists of a front-end circuit connected to a packaged silicone-coated resistive-bridge pressure sensor for detecting APW through direct skin contact in a non-invasive manner. Compared to other pulse sensing approaches, the proposed front-end only requires an instrumentation amplifier (IA) and a low-pass filtering analog-to-digital converter (LPF-ADC), and consumes a total power of 10 μW. An automatic calibration circuit is proposed to compensate for the resistive-bridge offset and can reduce such offset down to 1 mV. High linearity in the IA is provided through the use of a super class-AB output stage. A LPF-ADC architecture is employed to extract and digitize the APW in a 100 Hz bandwidth, saving 90 % of the passives area. The front-end provides a measured input-referred noise of 7.2 μVrms with a gain of 32-40 dB, and a THD of -74.6 dB. Together with an on-chip low dropout regulator (LDO) and a buffer stage, the prototype fabricated in 0.18 μm CMOS technology has an active area of 0.52 mm
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Year | DOI | Venue |
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2019 | 10.1109/A-SSCC47793.2019.9056943 | 2019 IEEE Asian Solid-State Circuits Conference (A-SSCC) |
Keywords | DocType | ISBN |
THD arterial pulse waveform sensing system,automatic bridge-offset calibration,super class-AB output stage,highly-linear sensing system,arterial pulse waveform acquisition,APW,front-end circuit,packaged silicone-coated resistive-bridge pressure sensor,direct skin contact,analog-to-digital converter,automatic calibration circuit,LPF-ADC architecture,buffer stage,power 10.0 muW,voltage 1.0 mV,size 0.18 mum,bandwidth 100.0 Hz,gain 32.0 dB to 40.0 dB | Conference | 978-1-7281-5107-6 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Yu-Pin Hsu | 1 | 0 | 0.34 |
Zemin Liu | 2 | 64 | 12.71 |
Mona Mostafa Hella | 3 | 68 | 14.51 |