Glucolynx-App

Glucolynx app is a simple blood glucose monitoring application by using Near-Infrared Spectroscopy (NIRS). Machine Learning algorithms in MATLAB are used to predict blood glucose level. NIR data are generated as .csv files by DLP® NIRscan™ Nano Evaluation Module from Texas Instruments from scanning fingertips. By default, this code will extract the absorbance data from .csv file.

Getting Started

MATLAB (above R2016a) must be installed on local machine.

Installation

If you want to run the latest code from git, here's how to get started:

1. Clone the code:

    git clone https://github.com/theinhtut/glucolynx.git
    cd glucolynx
   

2. Open MATLAB and run

    run('glucolynxApp.m');
   

Built With

• MATLAB R2018a - Multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks.
• MATLAB App Designer - A rich development environment that provides layout and code views, a fully integrated version of the MATLAB® editor.

Version

Glucolynx-App v1.0.0

Authors

• Thein Htut - Glucolynx-App - Github

• Lars Nørgaard - iPLS Toolbox for MATLAB - [email protected] FOSS Affiliated professor in Chemometrics Group, Quality & Technology University of Copenhagen Denmark

• Riccardo Leardi, - iPLS Toolbox for MATLAB: bipls & bipls_dyn - [email protected] Department of Pharmaceutical and Food Chemistry and Technology University of Genoa Italy

See also the list of contributors who participated in this project.

References

L. Nørgaard, A. Saudland, J. Wagner, J.P. Nielsen, L. Munck and S.B. Engelsen, Interval Partial Least Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy, Applied Spectroscopy, 54, 413-419, 2000.

R. Leardi and L. Nørgaard, Sequential application of backward interval-PLS and Genetic Algorithms for the selection of relevant spectral regions, Journal of Chemometrics, 18, 486-497, 2004.

Publication

Non-Invasive Blood Glucose Estimation using Handheld Near Infra-Red Device
Mahmud Iwan Solihin, Yaameen Shameem, Thein Htut, Chun Kit Ang, Muzaiyanah bt Hidayab
International Journal of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Volume-8 Issue-3S, October 2019

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• Brillianda Sheravina - For awesome logo design ideas, application name and inspiration by love ❤
• Lars Nørgaard & Riccardo Leardi - Awesome iPLS Toolbox for MATLAB
• To anyone whose codes were used as reference.