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ORCIDGiovanni Sparacino
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- affiliation: University of Padua, Italy
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2020 – today
- 2024
[j56]Chiara Roversi
, Nunzio Camerlingo, Martina Vettoretti, Andrea Facchinetti, Pratik Choudhary, Giovanni Sparacino, Simone Del Favero:
Risk of hypoglycemia in type 1 diabetes management: An in-silico sensitivity analysis to assess and rank the quantitative impact of different behavioral factors. Comput. Methods Programs Biomed. 244: 107943 (2024)- [j55]Jacopo Pavan, Giulia Noaro, Andrea Facchinetti, Domenico Salvagnin, Giovanni Sparacino, Simone Del Favero:
A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management. Comput. Methods Programs Biomed. 250: 108179 (2024) - [j54]Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Pratik Choudhary, Giovanni Sparacino:
Corrigendum to "Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach". Comput. Methods Programs Biomed. 252: 108232 (2024) - 2023
- [j53]Martina Vettoretti, Martina Drecogna, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino:
A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials. Comput. Methods Programs Biomed. 240: 107700 (2023) - [j52]Giacomo Cappon, Francesco Prendin, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero:
Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-Box Approaches to a Physiological White-Box One. IEEE Trans. Biomed. Eng. 70(11): 3105-3115 (2023) - [j51]Giacomo Cappon, Martina Vettoretti, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
ReplayBG: A Digital Twin-Based Methodology to Identify a Personalized Model From Type 1 Diabetes Data and Simulate Glucose Concentrations to Assess Alternative Therapies. IEEE Trans. Biomed. Eng. 70(11): 3227-3238 (2023) - [j50]Jacopo Pavan, Domenico Salvagnin, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero:
Incorporating Sparse and Quantized Carbohydrates Suggestions in Model Predictive Control for Artificial Pancreas in Type 1 Diabetes. IEEE Trans. Control. Syst. Technol. 31(2): 570-586 (2023) - [c39]Enrico Longato, Erica Tavazzi, Adriano Chiò, Gabriele Mora, Giovanni Sparacino, Barbara Di Camillo:
Dealing with Data Scarcity in Rare Diseases: Dynamic Bayesian Networks and Transfer Learning to Develop Prognostic Models of Amyotrophic Lateral Sclerosis. AIME 2023: 140-150 - [c38]Giacomo Cappon, Elisa Pellizzari, Luca Cossu, Giovanni Sparacino, Annalisa Deodati, Riccardo Schiaffini, Stefano Cianfarani, Andrea Facchinetti:
System Architecture of TWIN: A New Digital Twin-Based Clinical Decision Support System for Type 1 Diabetes Management in Children. BSN 2023: 1-4 - [c37]Elena Idi, Francesco Prendin, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero:
Detection of compression artifacts in time-series data from continuous glucose monitoring sensors using matched filters. BSN 2023: 1-4 - [c36]Elisa Pellizzari, Francesco Prendin, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti:
A Deep-Learning Based Algorithm for the Management of Hyperglycemia in Type 1 Diabetes Therapy. BSN 2023: 1-4 - 2022
- [j49]Simone Faccioli, Iván Sala-Mira, José-Luis Díez, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero, Jorge Bondia:
Super-twisting-based meal detector for type 1 diabetes management: Improvement and assessment in a real-life scenario. Comput. Methods Programs Biomed. 219: 106736 (2022) - [j48]Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Pratik Choudhary, Giovanni Sparacino:
Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach. Comput. Methods Programs Biomed. 221: 106862 (2022) - [j47]Enrico Longato, Mario Luca Morieri, Giovanni Sparacino, Barbara Di Camillo, Annamaria Cattelan, Sara Lo Menzo, Marco Trevenzoli, Andrea Vianello, Gabriella Guarnieri, Federico Lionello, Angelo Avogaro, Paola Fioretto, Roberto Vettor, Gian Paolo Fadini:
Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes. Comput. Methods Programs Biomed. 221: 106873 (2022) - [j46]Francesco Prendin, José-Luis Díez, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti, Jorge Bondia:
Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions. Sensors 22(22): 8682 (2022) - [j45]Simone Faccioli, Andrea Facchinetti, Giovanni Sparacino, Gianluigi Pillonetto, Simone Del Favero:
Linear Model Identification for Personalized Prediction and Control in Diabetes. IEEE Trans. Biomed. Eng. 69(2): 558-568 (2022) - [c35]Elena Idi, Eleonora Manzoni, Giovanni Sparacino, Simone Del Favero:
Data-Driven Supervised Compression Artifacts Detection on Continuous Glucose Sensors. EMBC 2022: 1145-1148 - [c34]Maria Rubega, Emanuela Formaggio, Luciana Ciringione, Margherita Bertuccelli, Matilde Paramento, Giovanni Sparacino, Andrea Vianello, Stefano Masiero, Alessandra Del Felice:
Sleep spindles changes in people with previous COVID-19 infection. EMBC 2022: 4135-4138 - [c33]Alessandro Guazzo, Enrico Longato, Gian Paolo Fadini, Mario Luca Morieri, Giovanni Sparacino, Barbara Di Camillo:
Explainable Deep-Learning Model Reveals Past Cardiovascular Disease in Patients with Diabetes Using Free-Form Visit Reports. LOD (1) 2022: 430-443 - 2021
- [j44]Francesco Prendin, Simone Del Favero, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti:
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. Sensors 21(5): 1647 (2021) - [j43]Giulia Noaro, Giacomo Cappon, Martina Vettoretti, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy. IEEE Trans. Biomed. Eng. 68(1): 247-255 (2021) - [j42]Enrico Longato, Gian Paolo Fadini, Giovanni Sparacino, Angelo Avogaro, Lara Tramontan, Barbara Di Camillo:
A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims. IEEE J. Biomed. Health Informatics 25(9): 3608-3617 (2021) - [c32]Enrico Longato, Gian Paolo Fadini, Giovanni Sparacino, Angelo Avogaro, Barbara Di Camillo:
Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data. AIME 2021: 329-337 - [c31]Alessandro Guazzo, Alessandro Battaggia, Enrico Longato, Bruno Franco-Novelletto, Angelo Avogaro, Gian Paolo Fadini, Maurizio Cancian, Barbara Di Camillo, Giovanni Sparacino, Massimo Fusello:
Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores in the Diabetic Outpatient Clinic and Primary Care Settings. BIBM 2021: 2694-2699 - [c30]Nunzio Camerlingo, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti, Julia K. Mader, Pratik Choudhary, Simone Del Favero:
A Mathematical Formula to Determine the Minimum Continuous Glucose Monitoring Duration to Assess Time-in-ranges: Sensitivity Analysis Over the Parameters. EMBC 2021: 1435-1438 - [c29]Giulia Noaro, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti:
An Ensemble Learning Algorithm Based on Dynamic Voting for Targeting the Optimal Insulin Dosage in Type 1 Diabetes Management. EMBC 2021: 1828-1831 - [c28]Giacomo Cappon, Emanuele Pighin, Francesco Prendin, Giovanni Sparacino, Andrea Facchinetti:
A Correction Insulin Bolus Delivery Strategy for Decision Support Systems in Type 1 Diabetes. EMBC 2021: 1832-1835 - [c27]Giacomo Cappon, Giulia Noaro, Nunzio Camerlingo, Luca Cossu, Giovanni Sparacino, Andrea Facchinetti:
A New Decision Support System for Type 1 Diabetes Management. EMBC 2021: 1993-1996 - [c26]Martina Drecogna, Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino:
Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. EMBC 2021: 4379-4382 - 2020
- [j41]Maria Rubega, Fabio Scarpa, Debora Teodori, Anne-Sophie Sejling, Christian S. Frandsen, Giovanni Sparacino:
Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients. Entropy 22(1): 81 (2020) - [j40]Martina Vettoretti, Giacomo Cappon, Andrea Facchinetti, Giovanni Sparacino:
Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors. Sensors 20(14): 3870 (2020) - [c25]Giacomo Cappon, Lorenzo Meneghetti, Francesco Prendin, Jacopo Pavan, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes. KDH@ECAI 2020: 75-79 - [c24]Jacopo Pavan, Francesco Prendin, Lorenzo Meneghetti, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero:
Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. KDH@ECAI 2020: 95-99 - [c23]Francesca Marturano, Sabrina Brigadoi, Mattia Doro, Roberto Dell'Acqua, Giovanni Sparacino:
A Time-Frequency Analysis for the Online Detection of the N2pc Event-Related Potential (ERP) Component in Individual EEG Datasets. EMBC 2020: 1019-1022 - [c22]Giulia Noaro, Giacomo Cappon, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
Nonlinear Machine Learning Models for Insulin Bolus Estimation in Type 1 Diabetes Therapy. EMBC 2020: 5502-5505
2010 – 2019
- 2019
- [j39]Giacomo Cappon, Andrea Facchinetti, Giovanni Sparacino, Pantelis Georgiou, Pau Herrero:
Classification of Postprandial Glycemic Status with Application to Insulin Dosing in Type 1 Diabetes - An In Silico Proof-of-Concept. Sensors 19(14): 3168 (2019) - [j38]Giada Acciaroli, Mattia Zanon, Andrea Facchinetti, Andreas Caduff, Giovanni Sparacino:
Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device. Sensors 19(17): 3677 (2019) - [j37]Martina Vettoretti, Cristina Battocchio, Giovanni Sparacino, Andrea Facchinetti:
Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime. Sensors 19(23): 5320 (2019) - [c21]Martina Vettoretti, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti:
Modeling the error of factory-calibrated continuous glucose monitoring sensors: application to Dexcom G6 sensor data. EMBC 2019: 750-753 - [c20]Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti:
In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes. EMBC 2019: 4133-4136 - [c19]Enrico Longato, Barbara Di Camillo, Giovanni Sparacino, Claudio Saccavini, Arianna Cocchiglia, Lara Tramontan, Gian Paolo Fadini:
Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy). EMBC 2019: 4293-4296 - [c18]Giacomo Cappon, Andrea Facchinetti, Giovanni Sparacino, Simone Del Favero:
A Bayesian Framework to Identify Type 1 Diabetes Physiological Models Using Easily Accessible Patient Data. EMBC 2019: 6914-6917 - 2018
- [j36]Enrico Longato, Giada Acciaroli, Andrea Facchinetti, Liisa Hakaste, Tuomi Tiinamaija, Alberto Maran, Giovanni Sparacino:
Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data. Comput. Biol. Medicine 96: 141-146 (2018) - [j35]Giada Acciaroli, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework. IEEE Trans. Biomed. Eng. 65(3): 587-595 (2018) - [j34]Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments. IEEE Trans. Biomed. Eng. 65(6): 1281-1290 (2018) - [c17]Giacomo Cappon, Martina Vettoretti, Francesca Marturano, Andrea Facchinetti, Giovanni Sparacino:
Optimal Insulin Bolus Dosing in Type 1 Diabetes Management: Neural Network Approach Exploiting CGM Sensor Information. EMBC 2018: 1-4 - [c16]Giada Acciaroli, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino:
Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management. EMBC 2018: 29-32 - [c15]Giada Acciaroli, Andrea Facchinetti, Gianluigi Pillonetto, Giovanni Sparacino:
Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models. EMBC 2018: 3630-3633 - 2017
- [j33]Fabio Scarpa, Maria Rubega, Mattia Zanon, Francesca Finotello, Anne-Sophie Sejling, Giovanni Sparacino:
Hypoglycemia-induced EEG complexity changes in Type 1 diabetes assessed by fractal analysis algorithm. Biomed. Signal Process. Control. 38: 168-173 (2017) - [j32]Maria Rubega, Claudia Cecchetto, Stefano Vassanelli, Giovanni Sparacino:
Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source Code Biol. Medicine 12(1): 3 (2017) - 2016
- [j31]Martina Vettoretti, Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Claudio Cobelli:
Online Calibration of Glucose Sensors From the Measured Current by a Time-Varying Calibration Function and Bayesian Priors. IEEE Trans. Biomed. Eng. 63(8): 1631-1641 (2016) - [j30]Guglielmo Frigo, Sabrina Brigadoi, Giada Giorgi, Giovanni Sparacino, Claudio Narduzzi:
Measuring Cerebral Activation From fNIRS Signals: An Approach Based on Compressive Sensing and Taylor-Fourier Model. IEEE Trans. Instrum. Meas. 65(6): 1310-1318 (2016) - 2015
- [j29]Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Claudio Cobelli:
Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices. Medical Biol. Eng. Comput. 53(12): 1259-1269 (2015) - [c14]Maria Rubega, Claudia Cecchetto, Stefano Vassanelli, Giovanni Sparacino:
Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex. EMBC 2015: 1520-1523 - [c13]Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Accuracy of devices for self-monitoring of blood glucose: A stochastic error model. EMBC 2015: 2359-2362 - [c12]Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment. EMBC 2015: 2363-2366 - [c11]Maria Rubega, Giovanni Sparacino, Anne-Sophie Sejling, Claus Bogh Juhl, Claudio Cobelli:
Decrease of EEG Coherence during hypoglycemia in type 1 diabetic subjects. EMBC 2015: 2375-2378 - [c10]Guglielmo Frigo, Sabrina Brigadoi, Giada Giorgi, Giovanni Sparacino, Claudio Narduzzi:
A compressive sensing spectral model for fNIRS haemodynamic response de-noising. MeMeA 2015: 244-249 - [c9]Guglielmo Frigo, Maria Rubega, G. Lezziero, Roberto Fontana, Claudia Cecchetto, Stefano Vassanelli, Giovanni Sparacino, Matteo Bertocco:
A software-based platform for multichannel electrophysiological data acquisition. MeMeA 2015: 353-358 - 2014
- [j28]Anahita Goljahani, Costanza D'Avanzo, Stefano Silvoni, Paolo Tonin, Francesco Piccione, Giovanni Sparacino:
Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface. Comput. Math. Methods Medicine 2014: 731046:1-731046:9 (2014) - [j27]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information. Comput. Methods Programs Biomed. 113(1): 144-152 (2014) - [j26]Anahita Goljahani, Patrizia Silvia Bisiacchi, Giovanni Sparacino:
An EEGLAB plugin to analyze individual EEG alpha rhythms using the "channel reactivity-based method". Comput. Methods Programs Biomed. 113(3): 853-861 (2014) - [j25]Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Jessica Castle, W. Kenneth Ward, Claudio Cobelli:
Modeling the Glucose Sensor Error. IEEE Trans. Biomed. Eng. 61(3): 620-629 (2014) - [j24]Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Improving Accuracy and Precision of Glucose Sensor Profiles: Retrospective Fitting by Constrained Deconvolution. IEEE Trans. Biomed. Eng. 61(4): 1044-1053 (2014) - [c8]Chiara Fabris, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Sparse Principal Component Analysis for the parsimonious description of glucose variability in diabetes. EMBC 2014: 6643-6646 - 2013
- [j23]Chiara Fabris, Wladimiro De Colle, Giovanni Sparacino:
Voice disorders assessed by (cross-) Sample Entropy of electroglottogram and microphone signals. Biomed. Signal Process. Control. 8(6): 920-926 (2013) - [j22]Costanza D'Avanzo, Anahita Goljahani, Gianluigi Pillonetto, Giuseppe De Nicolao, Giovanni Sparacino:
A multi-task learning approach for the extraction of single-trial evoked potentials. Comput. Methods Programs Biomed. 110(2): 125-136 (2013) - [j21]Mattia Zanon, Giovanni Sparacino, Andrea Facchinetti, Mark Talary, Andreas Caduff, Claudio Cobelli:
Regularised Model Identification Improves Accuracy of Multisensor Systems for Noninvasive Continuous Glucose Monitoring in Diabetes Management. J. Appl. Math. 2013: 793869:1-793869:10 (2013) - [j20]Fabio Scarpa, Sabrina Brigadoi, Simone Cutini, Pietro Scatturin, Marco Zorzi, Roberto Dell'Acqua, Giovanni Sparacino:
A reference-channel based methodology to improve estimation of event-related hemodynamic response from fNIRS measurements. NeuroImage 72: 106-119 (2013) - [j19]Mattia Zanon, Giovanni Sparacino, Andrea Facchinetti, Mark Talary, Martin Mueller, Andreas Caduff, Claudio Cobelli:
Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness. Sensors 13(6): 7279-7295 (2013) - [j18]Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Claudio Cobelli:
An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects. IEEE Trans. Biomed. Eng. 60(2): 406-416 (2013) - [c7]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Neural Network for Prediction of Glucose Concentration in Type 1 Diabetic Patients. SCAI 2013: 303-306 - 2012
- [j17]Mattia Zanon, Giovanni Sparacino, Andrea Facchinetti, Michela Riz, Mark Talary, Roland E. Suri, Andreas Caduff, Claudio Cobelli:
Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system. Medical Biol. Eng. Comput. 50(10): 1047-1057 (2012) - [j16]Anahita Goljahani, Costanza D'Avanzo, Sami Schiff, Piero Amodio, Patrizia Silvia Bisiacchi, Giovanni Sparacino:
A novel method for the determination of the EEG individual alpha frequency. NeuroImage 60(1): 774-786 (2012) - [j15]Giovanni Sparacino, Mattia Zanon, Andrea Facchinetti, Chiara Zecchin, Alberto Maran, Claudio Cobelli:
Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management. Sensors 12(10): 13753-13780 (2012) - [j14]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration. IEEE Trans. Biomed. Eng. 59(6): 1550-1560 (2012) - [j13]Stefania Guerra, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
Enhancing the Accuracy of Subcutaneous Glucose Sensors: A Real-Time Deconvolution-Based Approach. IEEE Trans. Biomed. Eng. 59(6): 1658-1669 (2012) - 2011
- [j12]Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
Online Denoising Method to Handle Intraindividual Variability of Signal-to-Noise Ratio in Continuous Glucose Monitoring. IEEE Trans. Biomed. Eng. 58(9): 2664-2671 (2011) - [c6]Fabio Scarpa, Sabrina Brigadoi, Simone Cutini, Pietro Scatturin, Marco Zorzi, Roberto Dell'Acqua, Giovanni Sparacino:
A methodology to improve estimation of stimulus-evoked hemodynamic response from fNIRS measurements. EMBC 2011: 785-788 - [c5]Mattia Zanon, Michela Riz, Giovanni Sparacino, Andrea Facchinetti, Roland E. Suri, Mark S. Talary, Claudio Cobelli:
Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring. EMBC 2011: 2538-2541 - [c4]Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Claudio Cobelli:
Detecting failures of the glucose sensor-insulin pump system: Improved overnight safety monitoring for Type-1 diabetes. EMBC 2011: 4947-4950 - [c3]Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Giuseppe De Nicolao, Claudio Cobelli:
A new neural network approach for short-term glucose prediction using continuous glucose monitoring time-series and meal information. EMBC 2011: 5653-5656 - 2010
- [j11]Giovanni Sparacino, Andrea Facchinetti, Claudio Cobelli:
"Smart" Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues. Sensors 10(7): 6751-6772 (2010) - [j10]Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli:
An Online Self-Tunable Method to Denoise CGM Sensor Data. IEEE Trans. Biomed. Eng. 57(3): 634-641 (2010)
2000 – 2009
- 2009
- [c2]Giovanni Sparacino, Wladimiro De Colle, D. De Luca, Edoardo Arslan:
Electroglottography and microphone signals assessed by approximate entropy in normal and dysphonic subjects. MAVEBA 2009: 77-79 - 2007
- [j9]Giovanni Sparacino, Francesca Zanderigo, Stefano Corazza, Alberto Maran, Andrea Facchinetti, Claudio Cobelli:
Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series. IEEE Trans. Biomed. Eng. 54(5): 931-937 (2007) - 2006
- [j8]Gianluigi Pillonetto, Andrea Caumo, Giovanni Sparacino, Claudio Cobelli:
A new dynamic index of insulin sensitivity. IEEE Trans. Biomed. Eng. 53(3): 369-379 (2006) - [c1]Andrea Facchinetti, Giovanni Sparacino, Francesca Zanderigo, Claudio Cobelli:
Reconstructing by Deconvolution Plasma Glucose from Continuous Glucose Monitoring Sensor Data. EMBC 2006: 55-58 - 2004
- [j7]Alessandra Bertoldo, Giovanni Sparacino, Claudio Cobelli:
"Population" approach improves parameter estimation of kinetic models from dynamic PET data. IEEE Trans. Medical Imaging 23(3): 297-306 (2004) - 2002
- [j6]Giovanni Sparacino, Gianluigi Pillonetto, Massimo Capello, Giuseppe De Nicolao, Claudio Cobelli:
WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems. Comput. Methods Programs Biomed. 67(1): 67-77 (2002) - [j5]Giovanni Sparacino, Stefano Milani, Edoardo Arslan, Claudio Cobelli:
A Bayesian approach to estimate evoked potentials. Comput. Methods Programs Biomed. 68(3): 233-248 (2002) - 2001
- [j4]Gianluigi Pillonetto, Giovanni Sparacino, Claudio Cobelli:
Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method. IEEE Trans. Biomed. Eng. 48(11): 1352-1354 (2001) - 2000
- [j3]Giuseppe De Nicolao, Giancarlo Ferrari-Trecate, Giovanni Sparacino:
Fast spline smoothing via spectral factorization concepts. Autom. 36(11): 1733-1739 (2000) - [j2]Giovanni Sparacino, Chiara Tombolato, Claudio Cobelli:
Maximum-likelihood versus maximum a posteriori parameter estimation of physiological system models: the c-peptide impulse response case study. IEEE Trans. Biomed. Eng. 47(6): 801-811 (2000)
1990 – 1999
- 1997
- [j1]Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli:
Nonparametric input estimation in physiological systems: Problems, methods, and case studies. Autom. 33(5): 851-870 (1997)
Coauthor Index
[j56] [j55] [j54] [j53] [j52] [j51] [j50] [c38] [c37] [c36] [j49] [j48] [j46] [j45] [j44] [j43] [c30] [c29] [c28] [c27] [c26] [j40] [c25] [c24] [c22] [j39] [j38] [j37] [c21] [c20] [c18] [j36] [j35] [j34] [c17] [c16] [c15] [j31] [j29] [c13] [c12] [j27] [j25] [j24] [c8] [j21] [j19] [j18] [c7] [j17] [j15] [j14] [j13] [j12] [c5] [c4] [c3] [j11] [j10] [j9] [c1]