Broadband polarimetric glucose determination in protein containing media using characteristic optical rotatory dispersion

Stark, Christian; Arrieta, Cesar Andres Carvajal; Behroozian, Reza; Redmer, Benjamin; Fiedler, Felix; Müller, Stefan

doi:10.1364/boe.10.006340

Cited by 16 publications

(5 citation statements)

References 32 publications

(74 reference statements)

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“…However, the presence of albumin concentrations in the interstitial fluid can skew accurate results. Stark, Arrieta [33] developed a broadband polarimeter setup that uses a Partial Least Squares (PLS) regression algorithm to distinguish between glucose and albumin based on their optical property characteristics. The method showed improved accuracy, allowing for more precise prediction of glucose concentration in the presence of albumin.…”

Section: Optical Polarimetry (Op)mentioning

confidence: 99%

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Di Filippo,

Sunstrum,

Khan

et al. 2023

Sensors

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Diabetes Mellitus incidence and its negative outcomes have dramatically increased worldwide and are expected to further increase in the future due to a combination of environmental and social factors. Several methods of measuring glucose concentration in various body compartments have been described in the literature over the years. Continuous advances in technology open the road to novel measuring methods and innovative measurement sites. The aim of this comprehensive review is to report all the methods and products for non-invasive glucose measurement described in the literature over the past five years that have been tested on both human subjects/samples and tissue models. A literature review was performed in the MDPI database, with 243 articles reviewed and 124 included in a narrative summary. Different comparisons of techniques focused on the mechanism of action, measurement site, and machine learning application, outlining the main advantages and disadvantages described/expected so far. This review represents a comprehensive guide for clinicians and industrial designers to sum the most recent results in non-invasive glucose sensing techniques’ research and production to aid the progress in this promising field.

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Section: Optical Polarimetry (Op)mentioning

confidence: 99%

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Di Filippo,

Sunstrum,

Khan

et al. 2023

Sensors

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show abstract

“…Optical rotatory dispersion (ORD) has attracted great attention due to its extensive application fields such as sugar manufacturing, pharmaceutical and chemical industries, environmental monitoring, and biomedical analysis [1][2][3][4][5][6] . So far there have been two main approaches to measuring the ORD curve.…”

Section: Introductionmentioning

confidence: 99%

Fast optical rotation dispersion measurement by using polarization axis finder and conical lens

Wang

Lei

Gao

et al. 2023

AOPC 2022: Optical Sensing, Imaging, and Display Technology

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Optical rotatory dispersion (ORD) is an important property of chiral material. How to obtain the ORD curve of chiral material quickly and accurately has attracted great attention from researchers. This work presents a measurement method of ORD based on a polarization axis finder (PAF) and a conical lens (CL). The PAF can modulate the collimated broadspectrum beam spatially to form an "hourglass" intensity pattern, and the CL can disperse the polarization information of light of different wavelengths to different positions in space. The use of the PAF and the CL enables the ORD of the sample to be obtained with only a single image. We perform a theoretical analysis of this method to prove it is feasible and verify it experimentally with left-hand quartz (LHQ) as the sample. Both theoretical and experimental results prove that this method is a fast and effective way to determine the ORD of chiral substances.

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“…There is room to improve the performance of non-invasive glucose sensors for public use under regular home conditions. These non-invasive glucose measurement techniques are based on infrared spectroscopy [6]- [8], Raman spectroscopy [9], [10], polarimetry [11], photoacoustic spectroscopy [12], millimeter wave/microwave spectroscopy [13]- [15], bio-impedance spectroscopy [16], optical coherence tomography [17], and hybrid techniques [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Glucose Monitoring Using Optical Sensor and Machine Learning Techniques for Diabetes Applications

et al. 2021

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Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be overcome before replacing the finger prick method. Also, the suitable employment of machine learning techniques can significantly improve the accuracy of glucose predictions. One aim of this study is to use light sources with multiple wavelengths to enhance the sensitivity and selectivity of glucose detection in an aqueous solution. Multiple wavelength measurements have the potential to compensate for errors associated with inter-and intra-individual differences in blood and tissue components. In this study, the transmission measurements of a custom built optical sensor are examined using 18 different wavelengths between 410 and 940 nm. Results show a high correlation value (0.98) between glucose concentration and transmission intensity for four wavelengths (485, 645, 860 and 940 nm). Five machine learning methods are investigated for glucose predictions. When regression methods are used, 9% of glucose predictions fall outside the correct range (normal, hypoglycemic or hyperglycemic). The prediction accuracy is improved by applying classification methods on sets of data arranged into 21 classes. Data within each class corresponds to a discrete 10 mg/dL glucose range. Classification based models outperform regression, and among them, the support vector machine is the most successful with F1-score of 99%. Additionally, Clarke error grid shows that 99.75% of glucose readings fall within the clinically acceptable zones. This is an important step towards critical diagnosis during an emergency patient situation.

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Broadband polarimetric glucose determination in protein containing media using characteristic optical rotatory dispersion

Cited by 16 publications

References 32 publications

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Fast optical rotation dispersion measurement by using polarization axis finder and conical lens

Non-Invasive Glucose Monitoring Using Optical Sensor and Machine Learning Techniques for Diabetes Applications

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