A Review: Non Invasive Sensing System for Detection Glucose Level

The calibration method is an alternative method that can be used to analyze the relationship between invasive and non-invasive blood glucose levels. Calibration modeling generally has a large dimension and contains multicolinearities because usually in functional data the number of independent variables (p) is greater than the number of observations (p>n). Both problems can be overcome using Functional Regression (FR) and Functional Principal Component Regression (FPCR). FPCR is based on Principal Component Analysis (PCA). In FPCR, the data is transformed using a polynomial basis before data reduction. This research tried to model the equations of spectral calibration of voltage value excreted by non-invasive blood glucose level monitoring devices to predict blood glucose using FR and FPCR. This study aimed to determine the best calibration model for measuring non-invasive blood glucose levels with the FR and FPCR. The results of this research showed that the FR model had a bigger coefficient determination (R2) value and lower Root Mean Square Error (RMSE) and Root Mean Square Error Prediction (RMSEP) value than the FPCR model, which was 12.9%, 5.417, and 5.727 respectively. Overall, the calibration modeling with the FR model is the best model for estimate blood glucose level compared to the FPCR model.

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NIR-based sensing system for non-Invasive detection of Hemoglobin for point-of-care applications

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405617666210823100316 ◽

2021 ◽

Vol 17 ◽

Author(s):

Yogesh Kumar ◽

Ayush Dogra ◽

Vikash Shaw ◽

Ajeet Kaushik ◽

Sanjeev Kumar

Keyword(s):

Linear Regression ◽

Point Of Care ◽

Principal Component ◽

Hemoglobin Concentration ◽

Multivariate Linear Regression ◽

Bulbar Conjunctiva ◽

Clinical Practices ◽

Non Invasive ◽

Sensing System ◽

Sliding Mechanism

Background: Hemoglobin is essential biomolecule for the transportation of oxygen therefore; its assessment is also obligatory very frequently in innumerable clinical practices. Traditional invasive techniques have concomitant shortcomings e.g. time delay, onset of infections and discomfort, which necessitates a non-invasive hemoglobin estimating solution to get rid of these constraints in health informatics. Currently various techniques are underway in allied domain and scanty products are also feasible in the market but due to low satisfaction rate, invasive solutions are still assumed as gold standard. Recently introduced technologies are effectively evolved as optical spectroscopy and digital photographic concepts on different sensing spots e.g. fingertip, palpebral conjunctiva, bulbar conjunctiva and fingernail. Productive sensors utilize more than eight wavelengths to compute hemoglobin concentration and four wavelengths to display only Hb-index (trending of hemoglobin) either in disposable adhesive or reusable clip type sensor’s configuration. Objective: This study aims an optimistic optical spectroscopic technique to measure hemoglobin concentration and conditional usability of non-invasive blood parameters’ diagnostics at point-of-care. Methods: Two distinguishable light emitting sources (810nm & 1300nm) are utilized at isosbestic points with single photodetector (800-1700nm). With this purpose, reusable finger probe assembly is facilitated in transmittance mode based on newly offered sliding mechanism to block ambient light. Results: Investigation with proposed design presents correlation coefficients between reference hemoglobin and every individual feature, multivariate linear regression model for highly correlated independent features. Moreover, principal component analytical model with multivariate linear regression offers mean bias of 0.036 & -0.316 g/dL, precision of 0.878 & 0.838 and limits of agreement from -1.685 to 1.758 g/dL & -1.790 to 1.474 g/dL for 18 & 21 principle components respectively. Conclusion: The encouraging readouts emphasize favorable precision therefore proposed sensing system is amenable to assess hemoglobin in settings with limited resources and strengthening future routes for point of care applications.

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A wearable electrochemical sensing system for non-invasive monitoring of lithium drug in bipolar disorder

IEEE Sensors Journal ◽

10.1109/jsen.2020.3009538 ◽

2020 ◽

pp. 1-1

Author(s):

Francesca Criscuolo ◽

Filippo Cantu ◽

Irene Taurino ◽

Sandro Carrara ◽

Giovanni De Micheli

Keyword(s):

Bipolar Disorder ◽

Electrochemical Sensing ◽

Invasive Monitoring ◽

Non Invasive ◽

Sensing System

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Study and Suppression of Multipath Signals in a Non-Invasive Millimeter Wave Transmission Glucose-Sensing System

IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology ◽

10.1109/jerm.2019.2938876 ◽

2020 ◽

Vol 4 (3) ◽

pp. 187-193

Author(s):

Maria Koutsoupidou ◽

Helena Cano-Garcia ◽

Roberto L. Pricci ◽

Shimul C. Saha ◽

George Palikaras ◽

...

Keyword(s):

Millimeter Wave ◽

Glucose Sensing ◽

Wave Transmission ◽

Non Invasive ◽

Sensing System ◽

Multipath Signals

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Analyzing Multivariate Calibration Techniques for Glucose Level Prediction in Non-invasive Human Tongue Spectra

10.1109/biotechno.2008.26 ◽

2008 ◽

Author(s):

S. R. Naqvi ◽

M. Saeed ◽

N. Azeemi

Keyword(s):

Glucose Level ◽

Multivariate Calibration ◽

Non Invasive ◽

Human Tongue ◽

Calibration Techniques

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A Non-Invasive Soil Moisture Sensing System Electronic Architecture: A Real Environment Assessment

Sensors ◽

10.3390/s20216147 ◽

2020 ◽

Vol 20 (21) ◽

pp. 6147

Author(s):

Leonardo Franceschelli ◽

Annachiara Berardinelli ◽

Marco Crescentini ◽

Eleonora Iaccheri ◽

Marco Tartagni ◽

...

Keyword(s):

Soil Moisture ◽

Electronic Circuit ◽

Silty Clay ◽

Non Invasive ◽

Fast Estimation ◽

Sensing System ◽

Real Environment ◽

Loam Soil ◽

Rapid Moisture ◽

Moisture Sensing

This paper will show the electronic architecture of a portable and non-invasive soil moisture system based on an open rectangular waveguide. The spectral information, measured in the range of 1.5–2.7 GHz, is elaborated on by an embedded predictive model, based on a partial least squares (PLS) regression tool, for the estimation of the soil moisture (%) in a real environment. The proposed system is composed of a waveguide, containing Tx and Rx antennas, and an electronic circuit driven by a microcontroller (MCU). It will be shown how the system provides a useful and fast estimation of moisture on a silty clay loam soil characterized by a moisture range of about 9% to 32% and a soil temperature ranging from about 8 °C and 18 °C. Using the PLS approach, the moisture content can be predicted with an R2 value of 0.892, a root mean square error (RMSE) of 1.0%, and a residual prediction deviation (RPD) of 4.3. The results prove that it is possible to make accurate and rapid moisture assessments without the use of invasive electrodes, as currently employed by state-of-the-art approaches.

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