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    Item type:Publication,
    Non-invasive Optical Blood Glucose Measuring System using Regression Models
    (2023-01-01)
    Limpiti, Tulaya
    ;
    Seemavijai, Mayravee
    ;
    Pongmee, Narutchai
    ;
    Kanayat, Pannita
    ;
    Koseeyaporn, Jeerasuda
    Diabetes is one of the chronic diseases with an increasing number of patients every year. Therefore, blood glucose level (BGL) is an essential health information for diagnosis and management of diabetes. Commonly, the BGL is usually measured invasively by taking blood samples, which can cause pain or discomfort to the patients. Our paper aims to design and develop a low-cost, low-computational non-invasive blood glucose measuring system using optical technique. The proposed system consists of a hardware for measuring photoplethysmogram (PPG). The PPG signal is subsequently analyzed to estimate the corresponding BGL, which is sent wirelessly to be stored in a database and displayed on an Android application. The application recommends the appropriate dosage of insulin injection based on the type of users and their diets. The report of historical blood glucose levels in the database can also be generated for further medical examination.Three PPG features, namely peak-to-peak amplitude, maximum amplitude, and standard deviation of signal amplitude, have the strongest correlations to the BGL. We investigate three regression models for estimating the BGL from these PPG parameters. The robustness of the system is assessed using cross validations. The average root mean squares error (RMSE) for three-fold cross-validations are 17.38, 16.76, and 16.39 mg/dL for simple linear regression, principal component regression, and partial least squares regression, respectively. The RMSEs from leave-one-out cross validation are approximately 12 mg/dL, with partial least squares regression model having the best accuracy. Furthermore, the results from Clarke Error Grid Analysis indicate that the system can be implemented with any of the three models for practical usage.
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    Chemometrics-assisted cross injection analysis for simultaneous determination of phosphate and silicate
    (2016-07-14)
    Uraisin, Kanchana
    ;
    Janya, Supavita
    ;
    Phechkrajang, Chutima
    ;
    Choengchan, Nathawut
    ;
    Tiyapongpattana, Warawut
    This work presents a novel method for simultaneous spectrophotometric determination of phosphate and silicate by using a cross injection analysis (CIA) coupled with the use of partial least squares (PLS) for data evaluation. The detection principle is based on the well-known ‘molybdenum blue’ method. The molybdate ions in the presence of stannous chloride in acidic medium give phosphomolybdenum blue and silicomolybdenum blue as products. In this work, all the liquids, including sample and reagents were simultaneously introduced into a CIA platform by using two peristaltic pumps for controlling the x-channel and y-channel flow which was automatically manipulated by using in-house control board. Crossflow provides sufficient mixing inside the platform prior detection of the absorption spectra of blue complexes in the wavelength of 400–900 nm. Since spectra of the blue colour product of phosphate and silicate are resemblant, these two analytes therefore reciprocally interfere with one another. This results in difficulty in simultaneous analysis of phosphate and silicate. In this work, PLS was utilised as assistor of CIA system for simultaneous analysis of phosphate and silicate using molybdenum blue reaction without using any modification of reagents and addition of selective masking agent. The calibration ranges are 0.1–6 mgP L<sup>−1</sup> and 5–100 mgSi L<sup>−1</sup> for phosphate and silicate, respectively. By using CIA coupled with PLS for data evaluation, the analysis of two analytes was achieved within 1.5 min with only single injection. The developed system was applied to natural water samples and the system was validated with the conventional methods. By statistical paired t-test, there was no evidence of significant difference at 95% confidence level (t<inf>stat</inf> = 2.28, t<inf>critical</inf> = 2.31 and t<inf>stat</inf> = 0.62, t<inf>critical</inf> = 2.31 for phosphate and silicate, respectively). This implied that the chemometrics-assisted CIA system was successfully developed for simultaneous spectrophotometric determination of phosphate and silicate.
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