A 186\mu \mathrm Glucose Monitoring SoC using Near-Infrared Photoplethysmography

A glucose monitoring SoC based on near-infrared Photoplethysmography (PPG) is presented. It integrates fully differential AFE with nonlinear support-vector-machine regression (NSVMR). The AFE utilizes chopper to reduce input-referred current noise by 57%, and trans-impedance amplifier input impedanc...

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Bibliographic Details
Published in2020 IEEE Asian Solid-State Circuits Conference (A-SSCC) pp. 1 - 4
Main Authors Hina, Aminah, Saadeh, Wala
Format Conference Proceeding
LanguageEnglish
Published IEEE 09.11.2020
Subjects
Diabetes
Glucose
glucose estimation
Impedance
Monitoring
non-invasive sensing
Photoplethysmography
Photoplethysmography (PPG)
Sensors
Solid state circuits
Support vector machines
wearable sensor
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DOI10.1109/A-SSCC48613.2020.9336124

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Summary:A glucose monitoring SoC based on near-infrared Photoplethysmography (PPG) is presented. It integrates fully differential AFE with nonlinear support-vector-machine regression (NSVMR). The AFE utilizes chopper to reduce input-referred current noise by 57%, and trans-impedance amplifier input impedance by 90%, thus allows 115dB dynamic range. The NSVMR is realized using the piecewise linear floating-point exponential, which decreases the area by 27% compared to conventional implementations. The 6mm 2 SoC in 0.18um CMOS consumes 186 \mu \mathrm{W} and reduces the mean absolute relative difference (mARD) by 30% verified on 200 subjects.
DOI:10.1109/A-SSCC48613.2020.9336124