Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches

Bent, Brinnae; Cho, Peter; Henriquez, Maria; Wittmann, April H.; Thacker, Connie R.; Feinglos, Mark N.; Crowley, Matthew J; Dunn, Jessilyn

doi:10.1038/s41746-021-00465-w

Cited by 47 publications

(38 citation statements)

References 90 publications

(72 reference statements)

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“…Advanced glycation end-products (AGE) were found to be deposited in the skin of individuals with T1D [46]. AGE can be measured using skin autofluorescence, which might serve as a non-invasive method to diagnose T1D [47]. Lastly, autoimmune diseases are often associated with other immune alterations, such as hypothyroidism and/or celiac disease.…”

Section: Diagnostic Methodsmentioning

confidence: 99%

Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care

et al. 2021

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Type 1 diabetes (T1D) is a complex autoimmune disease that currently cannot be cured, only managed. Optimal treatment the of T1D symptoms, requires a multidisciplinary care team, including endocrinologists, educators, primary care providers, health care specialists, genetic counselors, and data scientists. This review summarizes how an integrative approach to T1D drives innovation and quality improvements in health care. Specifically, we highlight how “-omics” technologies facilitate the understanding of different aspects of the disease, including prevention, pathogenesis, diagnostics, and treatment. Furthermore, we explore how biological data can be combined with personal and electronic health records to tailor medical interventions to the individual’s biology and lifestyle. We conclude that truly personalized medicine will not be limited to one data source but will emerge from the integration of multiple sources and disciplines that together will support individuals with T1D in their everyday life.

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Section: Diagnostic Methodsmentioning

confidence: 99%

Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care

et al. 2021

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“…An important place is given to fundamental research on certain aspects of health diagnostics and monitoring: interdisciplinary research of health mechanisms and affecting factors (Kooiker & Christiansen, 1995;van Doorslaer et al, 1997;Kogan, 206); creation of databases of valeological information (Nikiforova, 2011;Tolmacheva, 2015;European Database.., 2018); mathematical models (Kalachikova & Korchagina, 2015;Petrash & Murtazina, 2018;Jenatabadi et al, 2021;Wedlund & Kvedar, 2021); expert systems of evaluating health indicators (Allegra et al, 2020;Jespersen et al, 2021); and intellectual health support (Meyer, 2010;Chestnov et al, 2015;Kakani, 2020;Bent et al, 2021).…”

Section: What Does the Hls Concept Mean?mentioning

confidence: 99%

Promotion of a healthy lifestyle in Russia and China The first results of COVID-19 and trends in the post-COVID economy

Sharko

2021

BJE

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The COVID-19 pandemic has not only become a test for all mankind, but also gave reason to rethink the attitude to their health not only for people from the high-risk category, but also for everyone. Before the pandemic, the concept of a healthy lifestyle was gaining a powerful economic momentum (popularization of communities associated with fitness products, advertising, healthy products, etc.). But has the trend changed after the restrictions were eased? The purpose of this paper is to find out whether the healthy lifestyle concept affected the preservation of the health of the nation during the pandemic (is there a link between the level of national health and the degree of resistance to pandemics?). The study focuses on two countries — Russia and China. The difference in the population’s perception of the healthy lifestyle concept, promotion of a healthy lifestyle at the governmental level, and the assessment of its effectiveness are determined based on the analysis of secondary statistical data, a survey of 1,230 respondents from Russia and China in late 2020 — early 2021, as well as using econometric factor analysis. The results obtained can be scaled to the rest of the BRICS countries in order to adapt existing state programs to preserving the health of nations in the future.

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“…ring-resonator was proposed as a non-invasive glucose sensing 7 , 8 . Bent et al used smartwatches with food consumption records to track glucose 9 . Several methods were proposed for non-invasive glucose sensing; however, none of them could achieve both high accuracy and low cost at the same time.…”

Section: Introductionmentioning

confidence: 99%

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features

Srichan

Danvirutai³

et al. 2022

Sci Rep

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Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood glucose is in quest for better diagnosis, control and the management of diabetes mellitus (DM). Therefore, this study reports a multiple photonic band near-infrared (mbNIR) sensor augmented with personalized medical features (PMF) in Shallow Dense Neural Networks (SDNN) for the precise, inexpensive and pain free blood glucose determination. Datasets collected from 401 blood samples were randomized and trained with ten-fold validation. Additionally, a cohort of 234 individuals not included in the model training set were investigated to evaluate the performance of the model. The model achieved the accuracy of 97.8% along with 96.0% precision, 94.8% sensitivity and 98.7% specificity for DM classification based on a diagnosis threshold of 126 mg/dL for diabetes in fasting blood glucose. For non-invasive real-time blood glucose monitoring, the model exhibited ± 15% error with 95% confidence interval and the detection limit of 60–400 mg/dL, as validated with the standard hexokinase enzymatic method for glucose estimation. In conclusion, this proposed mbNIR based SDNN model with PMF is highly accurate and computationally cheaper compared to similar previous works using complex neural network. Some groups proposed using complicated mixed types of sensors to improve noninvasive glucose prediction accuracy; however, the accuracy gain over the complexity and costs of the systems harvested is still in questioned (Geng et al. in Sci Rep 7:12650, 2017). None of previous works report on accuracy enhancement of NIR/NN using PMF. Therefore, the proposed SDNN over PMF/mbNIR is an extremely promising candidate for the non-invasive real-time blood glucose monitoring with less complexity and pain-free.

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Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches

Cited by 47 publications

References 90 publications

Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care

Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care

Promotion of a healthy lifestyle in Russia and China The first results of COVID-19 and trends in the post-COVID economy

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features

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