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Abhijeet Dash
abhijeet@wrriten.com
Papers
Non-Invasive CGM
Glucose sensing review
NIR calibration notes
Datasets1
sample_timecourse_3d90×5
groupt_hmeascontrol05.0control65.2treated05.05treated65.67
References3
Yadav et al., 2015
Battelino et al., 2019
Saeedi et al., 2019
Images 2
ExportFormat· IEEEPreview

A Wrist-Worn Near-Infrared Sensor for Non-Invasive Continuous Glucose Monitoring

Abhijeet Dash, R. Iyer, S. Venkatesan

Continuous glucose monitoring has transformed glycemic management, yet every commercial system in wide use remains minimally invasive, relying on a subcutaneous filament replaced every one to two weeks.

Introduction

Diabetes affects an estimated 537 million adults worldwide, and effective management depends on frequent knowledge of blood glucose Saeedi et al., 2019. Continuous monitoring shifted care from sparse finger-stick measurements to dense, real-time traces, improving time in range Battelino et al., 2019. Adoption outside the insulin-dependent population nonetheless remains low, and the dominant barrier is the invasiveness of the sensor itself.

A truly non-invasive sensor, one that reads glucose through intact skin, has been pursued for three decades, with near-infrared spectroscopy the most studied optical route

Preview83%
IEEE Trans. Biomed. Eng.1
A Wrist-Worn Near-Infrared Sensor for Non-Invasive Continuous Glucose Monitoring
Abhijeet Dash, R. Iyer, S. Venkatesan
Abstract
1  Introduction
2  Method
Fig. 1: Reconstructed glucose trace against the reference CGM.
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Wrriten · sample_timecourse_3d
DataNotebook
#grouptimepoint_hmeasurement
1control05.0
2control05.1
3control65.2
4control125.1
5control245.0
6treated05.05
7treated65.67
8treated125.77
9treated245.85
Notebook
Run allSave
Text
Dose response surface
A 3D view of measurement across dose and timepoint.
Python
Run
piv = df.pivot_table(index='dose_mg', columns='timepoint_h',
values='measurement', aggfunc='mean')
surf = ax.plot_surface(X, Y, Z, cmap='viridis')
measurement
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IEEE Trans. Neural Netw.1
Attention Bottlenecks in Long-Context Sequence Models
A. Dash, R. Iyer, S. Venkatesan
Abstract
1  Introduction
2  Method
Fig. 1: Effective context utilisation vs. sequence length.

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Clinical Targets for Continuous Glucose Monitoring
Battelino et al. · 2019
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