Real-time improvement of continuous glucose monitoring accuracy: the smart sensor concept.

Objective: Reliability of continuous glucose monitoring (CGM) sensors is key in several applications. In this work we demonstrate that real-time algorithms can render CGM sensors smarter by reducing their uncertainty and inaccuracy and improving their ability to alert for hypo- and hyperglycemic events.

Research Design And Methods: The smart CGM (sCGM) sensor concept consists of a commercial CGM sensor whose output enters three software modules, able to work in real time, for denoising, enhancement, and prediction.

The role of foot morphology on foot function in diabetic subjects with or without neuropathy.

The aim of this study was to investigate the role of foot morphology, related with respect to diabetes and peripheral neuropathy in altering foot kinematics and plantar pressure during gait. Healthy and diabetic subjects with or without neuropathy with different foot types were analyzed. Three dimensional multisegment foot kinematics and plantar pressures were assessed on 120 feet: 40 feet (24 cavus, 20 with valgus heel and 11 with hallux valgus) in the control group, 80 feet in the diabetic (25 cavus 13 with valgus heel and 13 with hallux valgus) and the neuropathic groups (28 cavus, 24 with valgus heel and 18 with hallux valgus).

Bag of Naïve Bayes: biomarker selection and classification from genome-wide SNP data.

Background: Multifactorial diseases arise from complex patterns of interaction between a set of genetic traits and the environment. To fully capture the genetic biomarkers that jointly explain the heritability component of a disease, thus, all SNPs from a genome-wide association study should be analyzed simultaneously.

Results: In this paper, we present Bag of Naïve Bayes (BoNB), an algorithm for genetic biomarker selection and subjects classification from the simultaneous analysis of genome-wide SNP data.

Continuous glucose monitoring accuracy results vary between assessment at home and assessment at the clinical research center.

Background: Continuous glucose monitoring system (CGMS) accuracy is of critical importance both in delivering therapeutic value and as a component of a closed-loop system. This study aims at assessing the differences between accuracy assessments of CGMS at home and at the clinical research center (CRC).

Methods: Twelve patients with type 1 diabetes used the Dexcom® SEVEN® PLUS (DexCom, Inc.

Motion analysis of front crawl swimming applying CAST technique by means of automatic tracking.

Kinematic analysis of swimming is of interest to improve swimming performances. Although the video recordings of underwater swimmers are commonly used, the available methodologies are rarely precise enough to adequately estimate the three dimensional (3D) joint kinematics. This is mainly due to difficulties in obtaining the required kinematic parameters (anatomical landmarks, joint centres and reference frames) in the swimming environment.

Biomechanical assessment of balance and posture in subjects with ankylosing spondylitis.

Background: Ankylosing spondylitis is a major chronic rheumatic disease that predominantly affects axial joints, determining a rigid spine from the occiput to the sacrum. The dorsal hyperkyphosis may induce the patients to stand in a stooped position with consequent restriction in patients' daily living activities. The aim of this study was to develop a method for quantitatively and objectively assessing both balance and posture and their mutual relationship in ankylosing spondylitis subjects.

The effect of walking on postprandial glycemic excursion in patients with type 1 diabetes and healthy people.

Objective: Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and patients with type 1 diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms.

Postprandial improvement in insulin sensitivity after a single exercise session in adolescents with low aerobic fitness and physical activity.

The purpose of this study was to determine the acute and residual impact of a single exercise bout on meal glucose control in adolescents with habitually low physical activity. Twelve adolescents (seven females/five males, 14 ± 2 yr) completed three trials. One trial [No Exercise (No Ex)] was completed after refraining from vigorous activity for ≥ 3 d.

Diurnal pattern to insulin secretion and insulin action in healthy individuals.

Evaluation of the existence of a diurnal pattern of glucose tolerance after mixed meals is important to inform a closed-loop system of treatment for insulin requiring diabetes. We studied 20 healthy volunteers with normal fasting glucose (4.8 ± 0.

Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system.

Non-invasive continuous glucose monitoring (NI-CGM) sensors are still at an early stage of development, but, in the near future, they could become particularly appealing in diabetes management. Solianis Monitoring AG (Zurich, Switzerland) has proposed an approach for NI-CGM based on a multi-sensor concept, embedding primarily dielectric spectroscopy and optical sensors. This concept requires a mathematical model able to estimate glucose levels from the 150 channels directly measured through the Multisensor.

Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia.

Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous insulin infusion [CSII]), known as artificial pancreas, can help optimize glycemic control in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, and Montpellier. We tested two modular CLC constructs: standard control to range (sCTR), designed to augment pump plus CGM by preventing extreme glucose excursions; and enhanced control to range (eCTR), designed to truly optimize control within near normoglycemia of 3.

Pulsatile portal vein insulin delivery enhances hepatic insulin action and signaling.

Insulin is secreted as discrete insulin secretory bursts at ~5-min intervals into the hepatic portal vein, these pulses being attenuated early in the development of type 1 and type 2 diabetes mellitus (T2DM). Intraportal insulin infusions (pulsatile, constant, or reproducing that in T2DM) indicated that the pattern of pulsatile insulin secretion delivered via the portal vein is important for hepatic insulin action and, therefore, presumably for hepatic insulin signaling. To test this, we examined hepatic insulin signaling in rat livers exposed to the same three patterns of portal vein insulin delivery by use of sequential liver biopsies in anesthetized rats.

The disposition index: from individual to population approach.

To correctly evaluate the glucose control system, it is crucial to account for both insulin sensitivity and secretion. The disposition index (DI) is the most widely accepted method to do so. The original paradigm (hyperbolic law) consists of the multiplicative product of indices related to insulin sensitivity and secretion, but more recently, an alternative formula has been proposed with the exponent α (power function law).

Modular closed-loop control of diabetes.

Modularity plays a key role in many engineering systems, allowing for plug-and-play integration of components, enhancing flexibility and adaptability, and facilitating standardization. In the control of diabetes, i.e.

Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach.

Minimally invasive continuous glucose monitoring (CGM) sensors can greatly help diabetes management. Most of these sensors consist of a needle electrode, placed in the subcutaneous tissue, which measures an electrical current exploiting the glucose-oxidase principle. This current is then transformed to glucose levels after calibrating the sensor on the basis of one, or more, self-monitoring blood glucose (SMBG) samples.

Integrated kinematics-kinetics-plantar pressure data analysis: a useful tool for characterizing diabetic foot biomechanics.

The fundamental cause of lower-extremity complications in diabetes is chronic hyperglycemia leading to diabetic foot ulcer pathology. While the relationship between abnormal plantar pressure distribution and plantar ulcers has been widely investigated, little is known about the role of shear stress. Moreover, the mutual relationship among plantar pressure, shear stress, and abnormal kinematics in the etiology of diabetic foot has not been established.

Diabetes-associated common genetic variation and its association with GLP-1 concentrations and response to exogenous GLP-1.

The mechanisms by which common genetic variation predisposes to type 2 diabetes remain unclear. The disease-associated variants in TCF7L2 (rs7903146) and WFS1 (rs10010131) have been shown to affect response to exogenous glucagon-like peptide 1 (GLP-1), while variants in KCNQ1 (rs151290, rs2237892, and rs2237895) alter endogenous GLP-1 secretion. We set out to validate these observations using a model of GLP-1-induced insulin secretion.

Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.

Motivation: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the analysis.

Function-based discovery of significant transcriptional temporal patterns in insulin stimulated muscle cells.

Background: Insulin action on protein synthesis (translation of transcripts) and post-translational modifications, especially of those involving the reversible modifications such as phosphorylation of various signaling proteins, are extensively studied but insulin effect on transcription of genes, especially of transcriptional temporal patterns remains to be fully defined.

Methodology/principal Findings: To identify significant transcriptional temporal patterns we utilized primary differentiated rat skeletal muscle myotubes which were treated with insulin and samples were collected every 20 min for 8 hours. Pooled samples at every hour were analyzed by gene array approach to measure transcript levels.

Neural network incorporating meal information improves accuracy of short-time prediction of glucose concentration.

Diabetes mellitus is one of the most common chronic diseases, and a clinically important task in its management is the prevention of hypo/hyperglycemic events. This can be achieved by exploiting continuous glucose monitoring (CGM) devices and suitable short-term prediction algorithms able to infer future glycemia in real time. In the literature, several methods for short-time glucose prediction have been proposed, most of which do not exploit information on meals, and use past CGM readings only.

A glucose-specific metric to assess predictors and identify models.

In diabetes, the mean square error (MSE) metric is extensively used for assessing glucose prediction methods and identifying glucose models. One limitation of this metric is that, by equally treating errors in hypo-, eu-, and hyperglycemia, it is not able to weight the different clinical impact of errors in these three situations. In this paper, we propose a new cost function, which overcomes this limitation and can be used in place of MSE for several scopes, in particular for assessing the quality of glucose predictors and identifying glucose models.

Estimating Fugl-Meyer clinical scores in stroke survivors using wearable sensors.

Clinical assessment scales to evaluate motor abilities in stroke survivors could be used to individualize rehabilitation interventions thus maximizing motor gains. Unfortunately, these scales are not widely utilized in clinical practice because their administration is excessively time-consuming. Wearable sensors could be relied upon to address this issue.

A new neural network approach for short-term glucose prediction using continuous glucose monitoring time-series and meal information.

In the last decade, improvements in diabetes daily management have become possible thanks to the development of minimally-invasive portable sensors which allow continuous glucose monitoring (CGM) for several days. In particular, hypo and hyperglycemia can be promptly detected when glucose exceeds the normal range thresholds, and even avoided through the use of on-line glucose prediction algorithms. Several algorithms with prediction horizon (PH) of 15-30-45 min have been proposed in the literature, e.