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Giovanni 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
![](https://dblp1.uni-trier.de/img/cog.dark.24x24.png)
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last updated on 2024-08-05 21:14 CEST by the dblp team
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