Giovanni Sparacino

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"Population" approach improves parameter estimation of kinetic models from dynamic PET data

Alessandra Bertoldo, Giovanni Sparacino, Claudio Cobelli, 2004, IEEE Transactions on Medical Imaging.

Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2013, Sensors.

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, Comput. Biol. Medicine.

Retrofitting CGM traces

Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero, 2020 .

Neural Network for Prediction of Glucose Concentration in Type 1 Diabetic Patients

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2013, SCAI.

Glucose variability indices in type 1 diabetes: parsimonious set of indices revealed by sparse principal component analysis.

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2014, Diabetes technology & therapeutics.

Dexcom G4AP: An Advanced Continuous Glucose Monitor for the Artificial Pancreas

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2013, Journal of diabetes science and technology.

Online Denoising Method to Handle Intraindividual Variability of Signal-to-Noise Ratio in Continuous Glucose Monitoring

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2011, IEEE Transactions on Biomedical Engineering.

Assessing Minimum Continuous Glucose Monitoring Sensor Accuracy Needed for Non-Adjunctive Use

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2016 .

Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2007, IEEE Transactions on Biomedical Engineering.

Glucose sensors for diabetes management: no need of 24h warm-up time by the use of Bayes estimation

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2015, EMBC 2015.

“Algorithmically Smart” Continuous Glucose Sensor Concept for Diabetes Monitoring

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014 .

Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface

Giovanni Sparacino, Francesco Piccione, Stefano Silvoni, 2014, Comput. Math. Methods Medicine.

“Smart” Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2010, Sensors.

A Bayesian approach to estimate evoked potentials

Giovanni Sparacino, Claudio Cobelli, Stefano Milani, 2002, Comput. Methods Programs Biomed..

Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2012, Sensors.

A dynamic risk measure from continuous glucose monitoring data.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2011, Diabetes technology & therapeutics.

Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2018, IEEE Transactions on Biomedical Engineering.

Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Diabetes: Models, Signals, and Control

Giovanni Sparacino, Claudio Cobelli, Lalo Magni, 2009 .

Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, Journal of diabetes science and technology.

Fast spline smoothing via spectral factorization concepts

Giuseppe De Nicolao, Giovanni Sparacino, Giancarlo Ferrari-Trecate, 2000, Autom..

A software-based platform for multichannel electrophysiological data acquisition

Guglielmo Frigo, Stefano Vassanelli, Giovanni Sparacino, 2015, 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings.

A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements

Giovanni Sparacino, Sabrina Brigadoi, Simone Cutini, 2013, NeuroImage.

Modeling the Glucose Sensor Error

W. Kenneth Ward, Giovanni Sparacino, Claudio Cobelli, 2014, IEEE Transactions on Biomedical Engineering.

Enhanced accuracy of continuous glucose monitoring by online extended kalman filtering.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2010, Diabetes technology & therapeutics.

Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

In Silico Assessment of State-of-Art and New Algorithms for Real-time Basal Insulin Modulation in Sensor-Augmented Pumps

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2017 .

Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex

Stefano Vassanelli, Giovanni Sparacino, Claudia Cecchetto, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Simulation of Patient Decision-Making to Test Safety and Effectiveness of CGM Sensor for Non-Adjunctive Use in Type 1 Diabetes. I. A Patient Modular System Model

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2015 .

Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2001, IEEE Transactions on Biomedical Engineering.

Nonlinear Machine Learning Models for Insulin Bolus Estimation in Type 1 Diabetes Therapy

Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

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

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A new index to optimally design and compare continuous glucose monitoring glucose prediction algorithms.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2011, Diabetes technology & therapeutics.

Modeling the Error of Continuous Glucose Monitoring Sensor Data: Critical Aspects Discussed through Simulation Studies

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2010, Journal of diabetes science and technology.

Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction

Giovanni Sparacino, Simone Del Favero, Lorenzo Meneghetti, 2020, KDH@ECAI.

An analytical approach to determine the optimal duration of continuous glucose monitoring data required to reliably estimate time in hypoglycemia

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2020, Scientific Reports.

In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Jump neural network for real-time prediction of glucose concentration.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2015, Methods in molecular biology.

Next generation Dexcom sensor with Bayesian algorithm goes towards a calibration-free scenario

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2018 .

Support vector machine fed by CGM-based glycemic variability indices can distinguish between IGT and T2D subjects

Giovanni Sparacino, Andrea Facchinetti, Enrico Longato, 2017 .

Real-time detection of Glucose Sensor and Insulin Pump Faults in an Artificial Pancreas.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014 .

A Bayesian methodology to estimate single-trial ERPs with application to the study of the P300 variability in cirrhosis

Giovanni Sparacino, Steven J. Schiff, Costanza D'Avanzo, 2009 .

Simple Linear Support Vector Machine Classifier Can Distinguish Impaired Glucose Tolerance Versus Type 2 Diabetes Using a Reduced Set of CGM-Based Glycemic Variability Indices

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2020, Journal of diabetes science and technology.

Regularised Model Identification Improves Accuracy of Multisensor Systems for Noninvasive Continuous Glucose Monitoring in Diabetes Management

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2013, J. Appl. Math..

An Online Self-Tunable Method to Denoise CGM Sensor Data

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2010, IEEE Transactions on Biomedical Engineering.

Hypoglycemia-induced EEG complexity changes in Type 1 diabetes assessed by fractal analysis algorithm

Giovanni Sparacino, Mattia Zanon, Fabio Scarpa, 2017, Biomed. Signal Process. Control..

Sparse Principal Component Analysis for the parsimonious description of glucose variability in diabetes

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A methodology to improve estimation of stimulus-evoked hemodynamic response from fNIRS measurements

Giovanni Sparacino, Sabrina Brigadoi, Simone Cutini, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Decrease of EEG Coherence during hypoglycemia in type 1 diabetic subjects

Giovanni Sparacino, Claudio Cobelli, Maria Rubega, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

A Bayesian method to estimate single-trial event-related potentials with application to the study of the P300 variability

Giovanni Sparacino, Sami Schiff, Piero Amodio, 2011, Journal of Neuroscience Methods.

Improving Accuracy and Precision of Glucose Sensor Profiles: Retrospective Fitting by Constrained Deconvolution

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014, IEEE Transactions on Biomedical Engineering.

Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2017 .

Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Mapping hemodynamic changes during hypoglycemia in the very preterm neonatal brain: preliminary results

Giovanni Sparacino, Claudio Cobelli, Sabrina Brigadoi, 2019, European Conference on Biomedical Optics.

Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2019, Sensors.

Accuracy of devices for self-monitoring of blood glucose: A stochastic error model

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

A Time-Frequency Analysis for the Online Detection of the N2pc Event-Related Potential (ERP) Component in Individual EEG Datasets

Giovanni Sparacino, Sabrina Brigadoi, Mattia Doro, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Calibration of CGM systems

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2020 .

Reduced calibrations and maintained accuracy on next generation CGM compared to Dexcom G5: results using a Bayesian approach

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2016 .

Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device

Giovanni Sparacino, Mattia Zanon, Andrea Facchinetti, 2019, Sensors.

Maximum-likelihood versus maximum a posteriori parameter estimation of physiological system models: the c-peptide impulse response case study

Giovanni Sparacino, Claudio Cobelli, Chiara Tombolato, 2000, IEEE Transactions on Biomedical Engineering.

An EEGLAB plugin to analyze individual EEG alpha rhythms using the "channel reactivity-based method"

Giovanni Sparacino, Patrizia Silvia Bisiacchi, Anahita Goljahani, 2014, Comput. Methods Programs Biomed..

Computer data simulator to assess the accuracy of estimates of visual N2/N2pc event-related potential components

Giovanni Sparacino, Sabrina Brigadoi, Roberto Dell'Acqua, 2020, Journal of neural engineering.

A compressive sensing spectral model for fNIRS haemodynamic response de-noising

Guglielmo Frigo, Claudio Narduzzi, Giovanni Sparacino, 2015, 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings.

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2020, Sensors.

Electroglottography and microphone signals assessed by approximate entropy in normal and dysphonic subjects

Giovanni Sparacino, Edoardo Arslan, Wladimiro De Colle, 2009, MAVEBA.

A tunable local field potentials computer simulator to assess minimal requirements for phase–amplitude cross-frequency-coupling estimation

Stefano Vassanelli, Giovanni Sparacino, Maria Rubega, 2016, Network.

A stochastic deconvolution technique to estimate insulin secretion during IVGTT

Giovanni Sparacino, Claudio Cobelli, 1994 .

A new dynamic index of insulin sensitivity

Giovanni Sparacino, Claudio Cobelli, Andrea Caumo, 2006, IEEE Transactions on Biomedical Engineering.

Online Calibration of Glucose Sensors From the Measured Current by a Time-Varying Calibration Function and Bayesian Priors

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2016, IEEE Transactions on Biomedical Engineering.

Signal Processing Algorithms Implementing the “Smart Sensor” Concept to Improve Continuous Glucose Monitoring in Diabetes

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2013, Journal of diabetes science and technology.

Development of a Computer Simulator of the Visual N2 Event-Related Potential Component for the Study of Cognitive Processes

Giovanni Sparacino, Sabrina Brigadoi, Roberto Dell'Acqua, 2019, IFMBE Proceedings.

CGM filtering and denoising techniques

Giovanni Sparacino, Andrea Facchinetti, Claudio Cobelli, 2020 .

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

Giovanni Sparacino, Claudio Cobelli, Mattia Zanon, 2012, Medical & Biological Engineering & Computing.

Human brain hemodynamic activity elicited by visual short‐term memory in functional near infrared spectroscopy (fNIRS) assessed by a Bayesian filtering approach

Giovanni Sparacino, Simone Cutini, Roberto Dell'Acqua, 2010 .

Glucose Prediction Algorithms from Continuous Monitoring Data: Assessment of Accuracy via Continuous Glucose Error-Grid Analysis

Giovanni Sparacino, Claudio Cobelli, Boris P. Kovatchev, 2007, Journal of diabetes science and technology.

New Bayesian algorithm to reduce calibrations in continuous glucose monitoring sensors

Giovanni Sparacino, Martina Vettoretti, G. Acciaroli, 2018 .

Smart calibration of continuous glucose monitoring sensors: utility of Bayes estimation

Giovanni Sparacino, Claudio Cobelli, Martina Vettoretti, 2016 .

Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes—An In Silico Proof-of-Concept

Giovanni Sparacino, Andrea Facchinetti, Pantelis Georgiou, 2019, Sensors.

A multi-task learning approach for the extraction of single-trial evoked potentials

Giuseppe De Nicolao, Giovanni Sparacino, Gianluigi Pillonetto, 2013, Comput. Methods Programs Biomed..

Calibration of Minimally Invasive Continuous Glucose Monitoring Sensors: State-of-The-Art and Current Perspectives

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, Biosensors.

Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients

Giovanni Sparacino, Fabio Scarpa, Maria Rubega, 2020, Entropy.

Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation

Stefano Vassanelli, Giovanni Sparacino, Claudia Cecchetto, 2017, Source Code for Biology and Medicine.

A Model of Self-Monitoring Blood Glucose Measurement Error

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2017, Journal of diabetes science and technology.

Glucose Prediction Algorithms from Continuous Monitoring Data: Assessment of Accuracy via Continuous Glucose Error-Grid Analysis.

Giovanni Sparacino, Claudio Cobelli, Boris Kovatchev, 2007, Journal of diabetes science and technology.

Mathematical Models of Meal Amount and Timing Variability With Implementation in the Type-1 Diabetes Patient Decision Simulator

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2020, Journal of diabetes science and technology.

Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014, Comput. Methods Programs Biomed..

Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2018, IEEE Transactions on Biomedical Engineering.

In silico framework for testing and comparing bolus calculator optimization techniques based on CGM sensors

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2017 .

Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

A Bayesian Framework to Identify Type 1 Diabetes Physiological Models Using Easily Accessible Patient Data

Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy)

Giovanni Sparacino, Enrico Longato, Barbara Di Camillo, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2013, IEEE Transactions on Biomedical Engineering.

Chapter 3 – Deconvolution

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2001 .

Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2014, Medical & Biological Engineering & Computing.

Prediction-Based Alerting Methods CouldReduce Number and Duration of HypoglycemicEvents: An In Silico Quantification

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2012 .

Bayesian calibration algorithm for next generation Dexcom sensor: 8.4% MARD with one calibration every 4 days

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2017 .

Bayesian Identification of a Population Compartmental Model of C-Peptide Kinetics

Giovanni Sparacino, Claudio Cobelli, Riccardo Bellazzi, 2000, Annals of Biomedical Engineering.

Compartmental Models of Physiologic Systems (Chapter 159)

Giovanni Sparacino, Gianna Toffolo, Andrea Caumo, 2000 .

Enhancing the Accuracy of Subcutaneous Glucose Sensors: A Real-Time Deconvolution-Based Approach

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2012, IEEE Transactions on Biomedical Engineering.

STODEC (STOchastic DEConvolution): A Program for Input Estimation in Physiological and Pharmacokinetic Systems

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2000 .

Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy

Giovanni Sparacino, Martina Vettoretti, Simone Del Favero, 2020, IEEE Transactions on Biomedical Engineering.

Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2012, IEEE Transactions on Biomedical Engineering.

WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2002, Comput. Methods Programs Biomed..

Measuring Cerebral Activation From fNIRS Signals: An Approach Based on Compressive Sensing and Taylor–Fourier Model

Guglielmo Frigo, Claudio Narduzzi, Giovanni Sparacino, 2016, IEEE Transactions on Instrumentation and Measurement.

Voice disorders assessed by (cross-) Sample Entropy of electroglottogram and microphone signals

Giovanni Sparacino, Chiara Fabris, Wladimiro De Colle, 2013, Biomed. Signal Process. Control..

Nonparametric input estimation in physiological systems: Problems, methods, and case studies

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 1997, Autom..

Detecting failures of the glucose sensor-insulin pump system: Improved overnight safety monitoring for Type-1 diabetes

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes

Giovanni Sparacino, Simone Del Favero, Lorenzo Meneghetti, 2020, KDH@ECAI.

Data Gap Modeling in Continuous Glucose Monitoring Sensor Data

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data

Giovanni Sparacino, Enrico Longato, Barbara Di Camillo, 2021, AIME.

A New Decision Support System for Type 1 Diabetes Management

Giovanni Sparacino, Andrea Facchinetti, Giacomo Cappon, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

A Correction Insulin Bolus Delivery Strategy for Decision Support Systems in Type 1 Diabetes

Giovanni Sparacino, Andrea Facchinetti, Giacomo Cappon, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Linear Model Identification for Personalized Prediction and Control in Diabetes

Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero, 2022, IEEE Trans. Biomed. Eng..

Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2021, Sensors.

An Ensemble Learning Algorithm Based on Dynamic Voting for Targeting the Optimal Insulin Dosage in Type 1 Diabetes Management

Giovanni Sparacino, Andrea Facchinetti, Giacomo Cappon, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Diabetes and Prediabetes Classification Using Glycemic Variability Indices From Continuous Glucose Monitoring Data

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2018, Journal of diabetes science and technology.

Insulin Minimal Model Indexes and Secretion: Proper Handling of Uncertainty by a Bayesian Approach

Giovanni Sparacino, Claudio Cobelli, Riccardo Bellazzi, 2005, Annals of Biomedical Engineering.

econvolution Method to fter a Glucos

Giovanni Sparacino, Claudio Cobelli, C. Cobelli, 1996 .

Approximate Entropy Studies of Hormone Pulsatility from Plasma Concentration Time Series: Influence of the Kinetics Assessed by Simulation

Giovanni Sparacino, Claudio Cobelli, C. Cobelli, 2000, Annals of Biomedical Engineering.

Retrofitting Real-Life Dexcom G5 Data.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2017, Diabetes technology & therapeutics.

Continuous glucose monitoring and hypo/hyperglycaemia prediction

Giovanni Sparacino, Claudio Cobelli, Alberto Maran, 2006 .

Retrofitting of Continuous Glucose Monitoring Traces Allows More Accurate Assessment of Glucose Control in Outpatient Studies

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2015 .

Diabetes diagnosis from administrative claims and estimation of the true prevalence of diabetes among 4.2 million individuals of the Veneto region (North East Italy).

Giovanni Sparacino, Enrico Longato, Barbara Di Camillo, 2019, Nutrition, metabolism, and cardiovascular diseases : NMCD.

Postprandial glucose fluxes and insulin sensitivity during exercise: a study in healthy individuals.

Giovanni Sparacino, Claudio Cobelli, Ananda Basu, 2013, American journal of physiology. Endocrinology and metabolism.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2019, Diabetes & metabolism journal.

Electrocochleography Potentials Evoked by Condensation and Rarefaction Clicks Independently Derived by a New Numerical Filtering Approach

Giovanni Sparacino, Edoardo Arslan, Vincenzo Magnavita, 2000, Audiology and Neurotology.

Reconstruction of Glucose in Plasma from Interstitial Fluid Continuous Glucose Monitoring Data: Role of Sensor Calibration

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2007, Journal of diabetes science and technology.

A wavelet Methodology for EEG Time-frequency Analysis in a Time Discrimination Task

Giovanni Sparacino, Costanza D'Avanzo, Patrizia Bisiacchi, 2009 .

877-P: Limits of Correlation Coefficient Analysis in Determining the Minimal Duration of CGM Data Needed to Estimate Time Below Range

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2020, Diabetes.

Modeling Transient Disconnections and Compression Artifacts of Continuous Glucose Sensors.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2016, Diabetes technology & therapeutics.

Continuous glucose monitoring time series and hypo/hyperglycemia prevention: requirements, methods, open problems.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2008, Current diabetes reviews.

Deconvolution of Physiological and Pharmacokinetic Data: Comparison of Algorithms on Benchmark Problems

Giovanni Sparacino, Claudio Cobelli, 1997 .

Giovanni metabolic syndrome of impedance cardiography time series : effect of Hemodynamics assessed via approximate entropy analysis

Giovanni Sparacino, Stefania Guerra, Barbara Di Camillo, 2014 .

In Silico Assessment of Literature Methods to Adjust Insulin Bolus Dose according to CGM Trend

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2017 .

Numerical non-identifiability regions of the minimal model of glucose kinetics: superiority of Bayesian estimation.

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2003, Mathematical biosciences.

A Neural-Network-Based Approach to Personalize Insulin Bolus Calculation Using Continuous Glucose Monitoring

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2018, Journal of diabetes science and technology.

Physical activity measured by physical activity monitoring system correlates with glucose trends reconstructed from continuous glucose monitoring.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2013, Diabetes technology & therapeutics.

Predicting Insulin Treatment Scenarios with the Net Effect Method: Domain of Validity.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2016, Diabetes technology & therapeutics.

Handling Non-Negativity in Deconvolution of Physiological Signals: A Nonlinear Stochastic Approach

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2002, Annals of Biomedical Engineering.

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2018, Journal of diabetes science and technology.

Reduced sampling schedule for the glucose minimal model: importance of Bayesian estimation.

Giovanni Sparacino, Claudio Cobelli, Riccardo Bellazzi, 2006, American journal of physiology. Endocrinology and metabolism.

Toward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology.

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, Diabetes technology & therapeutics.

Hypoglycemia-Induced Decrease of EEG Coherence in Patients with Type 1 Diabetes.

Giovanni Sparacino, Claudio Cobelli, Maria Rubega, 2016, Diabetes technology & therapeutics.

Jonas Duun-Henriksen, Giovanni Sparacino, Claudio Cobelli, 2014, Diabetes technology & therapeutics.

Early hippocampal hyperexcitability in PS2APP mice: role of mutant PS2 and APP

Mufti Mahmud, Stefano Vassanelli, Giovanni Sparacino, 2017, Neurobiology of Aging.

Estimation of Organ Transport Function from Recirculating Indicator Dilution Curves

Giovanni Sparacino, Claudio Cobelli, C. Cobelli, 2004, Annals of Biomedical Engineering.

A Real-Time Continuous Glucose Monitoring Based Algorithm to Trigger Hypotreatments to Prevent/Mitigate Hypoglycemic Events.

Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, 2019, Diabetes technology & therapeutics.

Minimal model S(I)=0 problem in NIDDM subjects: nonzero Bayesian estimates with credible confidence intervals.

Giovanni Sparacino, Claudio Cobelli, Riccardo Bellazzi, 2002, American journal of physiology. Endocrinology and metabolism.

Spectral and Coherence Analysis of EEG during Intermittent Photic Stimulation in Patients with Photosensitive Epilepsy

Giovanni Sparacino, S. Franceschetti, Carlo Besta, 2009 .

Reconstruction of non-stationary biological signals via stochastic deconvolution

Giovanni Sparacino, Gianluigi Pillonetto, 2000 .

From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior.

Giovanni Sparacino, Claudio Cobelli, Andrea Facchinetti, 2016, Diabetes technology & therapeutics.