Giovanni Sparacino

Selected Publications

 

JOURNALS (List updated on June 5, 2017)

 

1.      Sparacino, G., C.Cobelli. A stochastic deconvolution approach to reconstruct insulin secretion rate after a glucose stimulus. IEEE Transactions on Biomedical Engineering 42: 512‑529, 1996.

2.      Sparacino, G., C. Cobelli. Reconstruction of insulin secretion by deconvolution: Domain of validity of a monoexponential impulse response model. Technology and Health Care 4: 87‑95, 1996.

3.      Sparacino, G., C. Cobelli. Impulse response model in reconstruction of insulin secretion by deconvolution. Role of input design in the identification experiment. Annals of Biomedical Engineering 25: 398‑416, 1997.

4.      Sparacino, G., Vicini, P., Bonadonna, R., Marraccini, P., Lehtovirta, M., Ferrannini, E., Cobelli, C. Removal of catheter distortion in multiple indicator dilution studies: A deconvolution‑based method and case studies on glucose blood‑tissue exchange. Medical & Biological Engineering & Computing 35: 337-342, 1997.

5.      Vicini, P., G. Sparacino, A.Caumo e C.Cobelli. Estimation of hepatic glucose release after a glucose perturbation by nonparametric stochastic deconvolution. Computer Methods and Programs in Biomedicine 52: 147‑156, 1997.

6.      De Nicolao, G., G. Sparacino e C.Cobelli. Nonparametric input estimation in physiological systems: problems, methods, case studies. Automatica 33: 851‑870, 1997.

7.      Sparacino, G., R.Bonadonna, H.Steinberg, A.Baron, e C.Cobelli. Estimation of organ transport function from recirculating indicator dilution curves. Annals of Biomedical Engineering 26: 128-137, 1998.

8.      Sparacino, G. , S. Milani, V. Magnavita, E.Arslan. Electrocochleography potentials evoked from condensation and rarefaction clicks independently derived by a new numerical filtering approach. Audiology & Neuro-Otology 5: 276-291, 2000.

9.      Sparacino, G., C.Tombolato, C.Cobelli. Maximum Likelihood vs Maximum a Posteriori Parameter Estimation of Physiological System Models: The C-peptide Impulse Response Case Study. IEEE Transactions on Biomedical Engineering 47: 801-811, 2000 .

10.   Sparacino, G., F. Bardi, C.Cobelli. Approximate Entropy studies of hormone pulsatility from plasma concentration time-series: influence of the kinetics assessed by simulation. Annals of Biomedical Engineering 28: 665 - 676, 2000.

11.   De Nicolao, G., G. Ferrari Trecate, G. Sparacino. Fast spline smoothing via spectral factorization concepts. Automatica 36: 1733-1739, 2000.

12.   Magni, P, Bellazzi, R, Sparacino, G C.Cobelli. Bayesian identification of a population compartmental model of C-peptide kinetics. Annals of Biomedical Engineering 28: 812-823, 2000.

13.   E.Arslan, R.Santarelli, G.Sparacino and G.Sella. Compound action potential and cochlear microphonic extracted from electrocochleographic responses to condensation or rarefaction clicks, Acta Otolaryngol 120:192-196, 2000.

14.   Pillonetto, G., G. Sparacino, and C. Cobelli. Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method. IEEE Transactions on Biomedical Engineering 48:1352-1354, 2001.

15.   Sparacino, G., G.Pillonetto, M.Capello, G. De Nicolao, C.Cobelli. Winstodec: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems. Computer Methods and Programs in Biomedicine 67: 67-77, 2002.

16.   Pillonetto, G., Sparacino, G., Magni, P., Bellazzi, R., Cobelli, C. Minimal model S(I)=0 problem in NIDDM subjects: nonzero Bayesian estimates with credible confidence intervals. American Journal of Physiology: Endocrinology and Metabolism, 282(3):E564-573, 2002

17.   Sparacino, G, D.M. Shames, P.Vicini, J.C. King, C.Cobelli. Domain of validity of the double isotope tracer method for measuring fractional zinc absorption: theoretical justification. American Journal of Physiology: Endocrinology and Metabolism 282: E679-687, 2002.

18.   Sparacino, G., S.Milani , E.Arslan, C.Cobelli. A Bayesian approach to estimate evoked potentials. Computer Methods and Programs in Biomedicine, 68: 233-2482, 2002.

19.   Pillonetto G, Sparacino G, Cobelli C. Handling non-negativity in deconvolution of physiological signals: a nonlinear stochastic approach. Annals of Biomededical Engineering, 30:1077-87, 2002.

20.   Pillonetto G, Sparacino G, Cobelli C. Numerical non-identifiability regions of the minimal model of glucose kinetics: superiority of Bayesian identification. Mathematical Biosciences, 184: 53-67, 2003.

21.   Bertoldo A, Sparacino G, Cobelli C. "Population" approaches improve parameter estimation of kinetic models from dynamic PET data. IEEE Transactions on Medical Imaging 23:297-306, 2004.

22.   Magni, P. G.Sparacino, R.Bellazzi, G.M. Toffolo, C.Cobelli. Insulin Minimal Model Indexes and Secretion: Proper Handling of Uncertainty by a Bayesian Approach. Annals of Biomedical Engineering Ann Biomed Eng:1027-37, 2004.

23.   Sparacino, G, R.Santarelli, A.Nale, E.Arslan. Deconvolution Method for Auditory Steady-State Responses. Medical & Biological Engineering & Computing 42(4):569-76, 2004.

24.   Magni P, Sparacino G, Bellazzi R, Cobelli C. Reduced sampling schedule for the glucose minimal model: importance of Bayesian estimation. Am J Physiol Endocrinol Metab. 290(1):E177-E184, 2006.

25.   Pillonetto G, Caumo A, Sparacino G, Cobelli C. A new dynamic index of insulin sensitivity. IEEE Trans Biomed Eng. 53(3):369-79, 2006.

26.   Sparacino, G. Zanderigo F., Maran A, Cobelli C. Continuous glucose Monitoring and Hypo/Hyperglycaemia Prediction  e , Diabetes Res Clin Pract. 74 Suppl 2:S160-3. 2006.

27.   Facchinetti, A, Sparacino G., Cobelli C.. Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration. Journal Of Diabetes Science And Technology. Vol. 1, pp. 617-623, 2007    

28.   Sparacino G., Zanderigo F, Corazza S, Maran A, Facchinetti A, Cobelli C.. Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time series. IEEE Transactions on Biomedical Engineering. Vol. 54, pp. 931-937, 2007

29.   Zanderigo, F, Sparacino G., Kovatchev B.P, Cobelli C. Glucose prediction algorithms from continuous monitoring data: assessment of accuracy via continuous glucose error-grid analysis. Journal Of Diabetes Science And Technology. Vol. 1, pp. 645-651, 2007

30.   Sparacino G., Facchinetti A, Maran A, Cobelli C. Continuous glucose monitoring time series and hypo/hyperglycemia prevention: requirements, methods, open problems. Curr Diabetes Rev. 4:181-192, 2008

31.   Amodio P, Orsato R, Marchetti P, Schiff S, Poci C, Angeli P, Gatta A, Sparacino G, Toffolo GM. Electroencephalographic analysis for the assessment of hepatic encephalopathy: comparison of non-parametric and parametric spectral estimation techniques. Neurophysiol Clin. 39:107-15, 2009.

32.   D’Avanzo, C., V.Tarantino, P. Bisiacchi, G. Sparacino. A wavelet methodology for EEG time-frequency analysis in a time discrimination task, International Journal of Bioelectromagnetism, Vol. 11, No. 4, pp.185-188, 2009

33.   G. Varotto, E.Visani, S. Franceschetti, G. Sparacino, F. Panzica. Spectral and Coherence Analysis of EEG during Intermittent Photic Stimulation in Patients with Photosensitive Epilepsy, International Journal of Bioelectromagnetism, Vol. 11, No. 4, pp.189-193, 2009.

34.   Cobelli, C. ; Dalla Man, C. ; Sparacino, G. ; Magni, L. ; De Nicolao, G. ; Kovatchev, B.P. Diabetes: Models, Signals, and Control. IEEE Reviews in Biomedical Engineering, 2, 54-96, 2009.

35.   Facchinetti A, Sparacino G, Cobelli C. Modeling the Error of Continuous Glucose Monitoring Sensor Data: Critical Aspects Discussed through Simulation Studies. J Diabetes Sci Technol. 2010 Jan 1;4(1):4-14.

36.   Pérez-Gandía C, Facchinetti A, Sparacino G, Cobelli C, Gómez EJ, Rigla M, de Leiva A, Hernando ME. Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring. Diabetes Technol Ther. 2010 Jan;12(1):81-8.

37.   Facchinetti A, Sparacino G, Cobelli C. An Online Self-Tunable Method to Denoise CGM Sensor Data. IEEE Trans Biomed Eng. 2010 Mar;57(3):634-41.

38.   Facchinetti A, Sparacino G, Cobelli C. Enhanced accuracy of continuous glucose monitoring by online extended kalman filtering. Diabetes Technol Ther. 2010 May;12(5):353-63.

39.   Sparacino G, Facchinetti A, Cobelli C. “Smart” Continuous Glucose Monitoring Sensors: On-Line Signal Processing Issues. Sensors 10 (7): 6751-6772, 2010.

40.   Facchinetti A, Sparacino G. Trifoglio E. Cobelli C. A New Index to Optimally Design and Compare CGM Glucose Prediction Algorithms, Diabetes Technol Ther. 2011 Feb;13(2):111-9.

41.   F. Scarpa, S. Cutini, P. Scatturin, R. Dell’Acqua, and G. Sparacino, "Bayesian filtering of human brain hemodynamic activity elicited by visual short-term maintenance recorded through functional near-infrared spectroscopy (fNIRS)," Opt. Express 18, 26550-26568 (2010)

42.   C. D’Avanzo, S.Shiff, P. Amodio, G.Sparacino A Bayesian method to estimate single-trial event-related potentials with application to the study of the P300 variability. J Neurosci Methods 198(1):114-24, 2011

43.   Vigili de Kreutzenberg S, Fadini GP, Boscari F, Rossi E, Guerra S, Sparacino G, Cobelli C, Ceolotto G, Bottero M, Avogaro A. Impaired hemodynamic response to meal intake in insulin-resistant subjects: an impedance cardiography approach. Am J Clin Nutr. 93:926-33, 2011.

44.   Guerra S, Sparacino G, Facchinetti A, Schiavon M, Dalla Man C, Cobelli C. A Dynamic Risk Measure from Continuous Glucose Monitoring Data. Diabetes Technol Ther. 2011 Aug;13(8):843-52.

45.   Guerra S, Boscari F, Avogaro A, Di Camillo B, Sparacino G, Vigili De Kreutzenberg S. Haemodynamics assessed via approximate entropy analysis of impedance cardiography time series: effect of metabolic syndrome. Am J Physiol Heart Circ Physiol. 2011 Aug;301(2):H592-8.

46.   Facchinetti A, Sparacino G, Cobelli C.Online Denoising Method to Handle Intra-Individual Variability of Signal-to-Noise Ratio in Continuous Glucose Monitoring. IEEE Trans Biomed Eng. 2011 Sep;58(9):2664-71.

47.   Marchetti P, D'Avanzo C, Orsato R, Montagnese S, Schiff S, Kaplan PW, Piccione F, Merkel C, Gatta A, Sparacino G, Toffolo GM, Amodio P. Electroencephalography Alterations in Patients with Cirrhosis. Gastroenterology. 2011 Nov;141(5):1680-1689.

48.   Goljahani A, D'Avanzo C, Schiff S, Amodio P, Bisiacchi P, Sparacino G. A novel method for the determination of the EEG individual alpha frequency, Neuroimage 60: 774–786, 2012.

49.   Zecchin C., Facchinetti A, Sparacino G, De Nicolao G, Cobelli C. Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration, IEEE Trans Biomed Eng 59(6):1550-60, 2012

50.   Guerra S, Facchinetti A, Sparacino G, De Nicolao G, Cobelli C. Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach, IEEE Trans Biomed Eng 59(6):1658-69, 2012.

51.   Zanon M, Sparacino G, Facchinetti A, Riz M, Talary MS, Suri RE, Caduff A, Cobelli C. Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system. Med. Biol. Eng. Comput. 2012, 50, 1047–1057.

52.   Sparacino G, M Zanon, A Facchinetti, C Zecchin, A Maran, C Cobelli. Italian Contributions to the Development of Continuous Glucose Monitoring Sensors for Diabetes Management Sensors 2012, 12(10), 13753-13780

53.   Zecchin, C. Facchinetti, A, Sparacino, G. and Cobelli, C. Reduction of Number and Duration of Hypoglycemic Events by Glucose Prediction Methods: A Proof-of-Concept In Silico Study. Diabetes Technol Ther. 2013 Jan;15(1):66-77.

54.   Facchinetti, A.; Sparacino, G.; Guerra, S.; Luijf, Y.M.; DeVries, J.H.; Mader, J.K.; Ellmerer, M.; Benesch, C.; Heinemann, L.; Bruttomesso, D.; Avogaro, A.; Cobelli, C.; on behalf of the AP at home Consortium. Real-time improvement of continuous glucose monitoring accuracy: the smart sensor concept. Diabetes Care 2013 Apr;36(4):793-800. doi: 10.2337/dc12-0736.

55.   Facchinetti, A, Del Favero, S., Sparacino, G. and Cobelli, C. An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects. IEEE Trans Biomed Eng. 2013 Feb;60(2):406-16.

56.   D’Avanzo C, Goljahani A, Pillonetto G, De Nicolao G., Sparacino G.. A multi-task learning approach for the extraction of single-trial evoked potentials. Comput Methods Programs Biomed. 2013 May;110(2):125-36. doi: 10.1016/j.cmpb.2012.11.001.

57.   Scarpa F, Brigadoi S, Cutini S, Scatturin P, Zorzi M, Dell'Acqua R, Sparacino G. A Reference-Channel Based Methodology to Improve Estimation of Event Related Hemodynamic Response from fNIRS Measurements. Neuroimage. 2013 May 15;72:106-19. doi: 10.1016/j.neuroimage.2013.01.021.

58.   Zanon, M.; Sparacino, G.; Facchinetti, A.; Talary, M.S.; Mueller, M.; Caduff, A.; Cobelli, C. Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness. Sensors 2013, 13, 7279-7295.

59.   Zecchin C, Facchinetti A, Sparacino G, Dalla Man C, Manohar C, Levine JA, Basu A, MD2, Kudva YC, Cobelli C. Physical activity measured by PAMS correlates with glucose trends reconstructed from CGM, Diabetes Technology and Therapeutics Diabetes Technol Ther. 2013 Oct;15(10):836-44. doi: 10.1089/dia.2013.0105. Epub 2013 Aug 14.

60.   Zanon, M, Sparacino G, Facchinetti A, Talary MS, Caduff A, Cobelli C. Regularised Model Identification Improves Accuracy of Multisensor Systems for Non-Invasive Continuous Glucose Monitoring in Diabetes Management, Journal of Applied Mathematics, vol. 2013, Article ID 793869, 10 pages, 2013. doi:10.1155/2013/793869

61.   Schiavon M, Hinshaw L, Mallad A, Dalla Man C, Sparacino G, Johnson ML, Carter RE, Basu R, Kudva YC, Cobelli C, Basu A. Postprandial Glucose Fluxes and Insulin Sensitivity during Exercise:A Study in Healthy Individuals. Am J Physiol Endocrinol Metab. 2013 Aug;305(4):E557-66. doi: 10.1152/ajpendo.00182.2013.

62.   Fabris C., De Colle W, Sparacino G. Voice Disorders Assessed by (Cross-) Sample Entropy of Electroglottogram and Microphone Signals. Biomedical Signal Processing and Control 8 (6) , pp. 920-926 2013.

63.   Facchinetti A., Sparacino G., Cobelli C. on behalf of the AP at home Consortium. Signal processing algorithms implementing the “smart sensor” concept to improve continuous glucose monitoring in diabetes. J Diabetes Sci Technol. 2013 Sep 1;7(5):1308-18.

64.   Schiff S., D’Avanzo C., Cona G., Goljahani A., Montagnese S., Volpato C., Gatta, A., Sparacino G., Bisiacchi P., Amodio P. Insight into the relationship between brain/behavioural speed and variability in patients with minimal hepatic encephalopathy. Clin Neurophysiol. 2014 Feb;125(2):287-97. doi: 10.1016/j.clinph.2013.08.004. Epub 2013 Sep 10.

65.   Facchinetti A, Del Favero S, Sparacino G, Castle J, Ward W, Cobelli C. Modeling the Glucose Sensor Error. IEEE Trans Biomed Eng. 2014 Mar;61(3):620-9. doi: 10.1109/TBME.2013.2284023. Epub 2013 Sep 30.

66.   C.Zecchin, A.Facchinetti, G. Sparacino, C. Cobelli Jump Neural Network for Online Short-Time Prediction of BloodGlucose from Continuous Monitoring Sensors and Meal Information. Comput Methods Programs Biomed. 2014 Jan;113(1):144-52. doi: 10.1016/j.cmpb.2013.09.016. Epub 2013 Oct 9.

67.   Garcia A, Rack-Gomer AL, Bhavaraju NC, Hampapuram H, Kamath A, Peyser T, Facchinetti A, Zecchin C, Sparacino G, Cobelli C. Dexcom G4AP: an advanced continuous glucose monitor for the artificial pancreas. J Diabetes Sci Technol. 2013 Nov 1;7(6):1436-45.

68.   Goljahani A, Bisiacchi P, Sparacino G. An EEGLAB plugin to analyze individual EEG alpha rhythms using the "channel reactivity-based method". Comput Methods Programs Biomed. 2014 Mar;113(3):853-61. doi: 10.1016/j.cmpb.2013.12.010. Epub 2013 Dec 31.

69.   Del Favero S, Facchinetti A, Sparacino G, Cobelli C. Improving accuracy and precision of glucose sensor profiles: retrospective fitting by constrained deconvolution. IEEE Trans Biomed Eng. 2014 Apr;61(4):1044-53. doi: 10.1109/TBME.2013.2293531.

70.   Fabris C, Sparacino G, Sejling AS, Goljahani A, Duun-Henriksen J, Remvig LS, Juhl CB, Cobelli C, Hypoglycemia-Related EEG Changes Assessed by Multiscale Entropy, Diabetes Technol Ther. 2014 Oct;16(10):688-94. doi: 10.1089/dia.2013.0331.

71.   Fabris C, Facchinetti A, Sparacino G, Zanon M, Guerra S, Maran A, Cobelli C,  Glucose Variability Indices in Type 1 Diabetes: Parsimonious Set of Indices Revealed by Sparse Principal Component Analysis, Diabetes Technol Ther. 2014 Oct;16(10):644-52. doi: 10.1089/dia.2013.0252.

72.   Goljahani A, D’Avanzo C, Silvoni S, Tonin P, Piccione F, Sparacino G, Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface, Computational and Mathematical Methods in Medicine, vol. 2014, Article ID 731046, 9 pages, 2014. doi:10.1155/2014/731046

73.   Facchinetti, A., Del Favero, S., Sparacino, G., Cobelli, C.Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices Med Biol Eng Comput. 2015 Dec;53(12):1259-69. doi: 10.1007/s11517-014-1226-y)

74.   Del Favero S, Facchinetti A, Sparacino G, Cobelli C. Retrofitting of continuous glucose monitoring traces allows more accurate assessment of glucose control in outpatient studies. Diabetes Technol Ther. 2015 May;17(5):355-63. doi: 10.1089/dia.2014.0230. Epub 2015 Feb 11.

75.   Vettoretti M, Facchinetti A, Del Favero S, Sparacino G, Cobelli C. On-line calibration of glucose sensors from the measured current by a time-varying calibration function and Bayesian priors. IEEE Trans Biomed Eng. 2015 Apr 24.

76.   Frigo, G., S. Brigadoi, G. Giorgi, G. Sparacino, C. Narduzzi. Measuring Cerebral Activation From fNIRS Signals: An Approach Based on Compressive Sensing and Taylor–Fourier Model IEEE Transactions on Instrumentation and Measurement Eng. 65, Vol. 6: 1310 - 1318, 2016,  DOI: 10.1109/TIM.2016.2518363

77.   Rubega M, Sparacino G, Sejling AS, Juhl CB, Cobelli C. Hypoglycemia-Induced Decrease of EEG Coherence in Patients with Type 1 Diabetes. Diabetes Technol Ther. 2016 Mar;18(3):178-84. doi: 10.1089/dia.2015.0347.

78.   Facchinetti A, Del Favero S, Sparacino G, Cobelli C. Modeling Transient Disconnections and Compression Artifacts of Continuous Glucose Sensors. Diabetes Technol Ther. 2016 Apr;18(4):264-72. doi: 10.1089/dia.2015.0250. Epub 2016 Feb 16.

79.   Zecchin C, Facchinetti A, Sparacino G, Cobelli C. How Much Is Short-Term Glucose Prediction in Type 1 Diabetes Improved by Adding Insulin Delivery and Meal Content Information to CGM Data? A Proof-of-Concept Study. J Diabetes Sci Technol. 2016 Aug 22;10(5):1149-60. doi: 10.1177/1932296816654161.

80.   G. Acciaroli, M. Vettoretti, A. Facchinetti, G. Sparacino, C. Cobelli. From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior. Diabetes Technol Ther. 2016 Volume 18, Number 8, 2016 DOI: 10.1089/dia.2016.0088

81.   M. Rubega, R. Fontana, S. Vassanelli, G. Sparacino. A tunable local field potentials computer simulator to assess minimal requirements for phase-amplitude cross-frequency-coupling estimation. Network: Computation in Neural Systems, 2016;27(4):268-288.

82.   Vettoretti M, Facchinetti A, Sparacino G, Cobelli C. Predicting Insulin Treatment Scenarios with the Net Effect Method: Domain of Validity. Diabetes Technol Ther. 2016 Nov;18(11):694-704.

83.   Fontana R, Agostini M, Murana E, Mahmud M, Scremin E, Rubega M, Sparacino G, Vassanelli S, Fasolato C. Early hippocampal hyperexcitability in PS2APP mice: role of mutant PS2 and APP. Neurobiol Aging. 2017 Feb;50:64-76. doi: 10.1016/j.neurobiolaging.2016.10.027.

84.   Rubega M, Sparacino G. Neurological Changes in Hypoglycemia. Diabetes Technol Ther. 2017 Feb;19(2):73-75. doi: 10.1089/dia.2017.0009.

85.   Rubega M, Cecchetto C, Vassanelli S, Sparacino G. Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source Code Biol Med. 2017 Feb 7;12:3. doi: 10.1186/s13029-017-0062-5.

86.   Vettoretti M, Facchinetti A, Sparacino G, Cobelli C. A Model of Self-Monitoring Blood Glucose Measurement Error. J Diabetes Sci Technol. 2017 Mar 1:1932296817698498. doi: 10.1177/1932296817698498.

87.   Del Favero S, Facchinetti A, Sparacino G, Cobelli C. Retrofitting Real-Life Dexcom G5 Data. Diabetes Technol Ther. 2017 Apr;19(4):237-245. doi: 10.1089/dia.2016.0413.

88.   G. Acciaroli, M. Vettoretti, A. Facchinetti, G. Sparacino, C. Cobelli. Reduction of blood glucose measurements to calibrate subcutaneous glucose sensors: a Bayesian multi-day framework. IEEE Transactions on Biomedical Engineering, Year: 2017 (in press), DOI: 10.1109/TBME.2017.2706974

89.   G.Acciaroli, G. Sparacino, L. Hakaste, A. Facchinetti, G.M, Di Nunzio, A. Palombit, T. Tuomi, R. Gabriel, J. Aranda, S. Vega, C. Cobelli. Diabetes and Prediabetes Classification Using Glycemic Variability Indices from Continuous Glucose Monitoring Data. Journal of Diabetes Science and Technology, DOI: 10.1177/1932296817710478, 2017 (in press)

90.   Scarpa F, Rubega M, Zanon M, Finotello F, Sejling AS, Sparacino G. Hypoglycemia-induced EEG complexity changes in Type 1 Diabetes assessed by fractal analysis algorithm, Biomedical Signal Processing and Control, doi: 10.1016/j.bspc.2017.06.004 (in press)

91.   E. Longato; M. Garrido; D. Saccardo; C. Montesinos Guevara; A. Mani; M. Bolognesi; P. Amodio; A. Facchinetti; G. Sparacino; S. Montagnese. Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin, Plos ONE 2017 (in press)

 

CHAPTERS IN BOOKS

 

1.      Sparacino, G., G.De Nicolao, C.Cobelli. Deconvolution. In: “E.Carson and C.Cobelli (Editors), Modeling Methodology for Physiology and Medicine (Biomedical Engineering Series)", Academic Press, San Diego, California, USA, pp. 45-76, 2001 (ISBN: 0121602451).

2.      Cobelli, C, Sparacino G., A.Caumo, M.P.Saccomani, E G.Toffolo. (2006). Compartmental Models of Physiologic Systems. In: J.Bronzino Editor. Biomedical Engineering Fundamentals (The Biomedical Engineering Handbook, 3rd Edition). (pp. 9.1-9.14). CRC Taylor & Francis (USA).

3.      Sparacino G, G Pillonetto, G De Nicolao, C Cobelli (2011). Deconvolution for Physiological Signal Analysis. In: S. Cerutti and C. Marchesi. Advanced Methods of Biomedical Signal Processing. p. 169-198, Hoboken, NJ: John Wiley & Sons, ISBN: 9780470422144, doi: 10.1002/9781118007747.ch8

4.      Cobelli, C, Sparacino G., A.Caumo, M.P.Saccomani, E G.Toffolo. (2006). Compartmental Models of Physiologic Systems. In: J.D. Bronzino, D.R. Peterson (Editors), Molecular, Cellular, and Tissue Engineering (Series: The Biomedical Engineering Handbook, Fourth Edition), CRC Press, 2015 ISBN 9781439825303

5.      G. Sparacino, G. De Nicolao, G.Pillonetto, C.Cobelli. Deconvolution. In “E.Carson and C.Cobelli (Editors), Modeling Methodology for Physiology and Medicine (Second Edition)", 2014, Pages 45–68, doi:10.1016/B978-0-12-411557-6.00003-3, Elsevier  (ISBN: 978-0-12-411557-6)

6.      P.Magni, G. Sparacino. “Chapter 5. Parameter Estimation”. In “E.Carson and C.Cobelli (Editors), Modeling Methodology for Physiology and Medicine (Second Edition)", Elsevier (ISBN 9780124115576), 2014, Pages 83–110, 2014, doi:10.1016/B978-0-12-411557-6.00005-7

7.      Zecchin, C.,  Facchinetti, A.,  Sparacino, G.,  Cobelli, C. Jump neural network for real-time prediction of glucose concentration. In: “Cartwright, H. (Editor, Artificial Neural Networks (Series: Methods in Molecular Biology)”, Volume 1260, 2015, Pages 245-259, Springer New York, doi: 10.1007/978-1-4939-2239-0_15

 

 

 

CONFERENCE PROCEEDINGS (after 2006)

 

1.      Facchinetti A., Sparacino G., Zanderigo F., Cobelli C.. “Reconstructing by Deconvolution Plasma from Continuous Monitoring Sensor Glucose: Domain of Validity of a Plasma-Interstitium Compartmental Model”. Proceedings of EMBS 2006, New York, NY, USA, 31 August-3 September 2006.

2.      Facchinetti A., Sparacino G., Zanderigo F., Cobelli C. “Prediction of Glucose Concentration from CGM Data through AR Time-Series Models: Role of Sampling Frequency and Other Design Variables”. Proceedings of Diabetes Technology Meeting 2006. Atlanta, Georgia,USA, November 2006.

3.      Facchinetti A., Vio E., Baruzzo T., Sparacino G., Cobelli C (2007). "On-Line Noise Removal of Continuous Glucose Monitoring (CGM) Data: Comparison of Filtering Techniques" Book of Abstracts, 7th Diabetes Technology Meeting, 25 - 27 October 2007, San Francisco (California - USA), pp A35.

4.      Facchinetti A., Baruzzo T., Vio E., Sparacino G., Cobelli C (2007). "On-Line Time-Series Prediction Models for Continuous Glucose Monitoring (CGM) Data". Book of Abstracts, 7th Diabetes Technology Meeting, 25 - 27 October 2007, San Francisco (California - USA), pp A36.

5.      Facchinetti A, Sparacino G, Cobelli C (2008). Hypoglycaemia prevention using CGM time-series: relative performance of different prediction methods. 27th Workshop of the AIDPIT Study Group, 2nd European Diabetes Technology and Transplantation Meeting (EuDTT), Igls / Austria, Jan 27-29, 2008

6.      Facchinetti A, Sparacino G, Cobelli C. (2008). An on-line bayesian filtering approach to deal with SNR variability of CGM data, 1st International Conference on Advanced Technologies and Treatments for Diabetes taking place in Prague, Czech Republic, February 27 – March 1, 2008.

7.      C. D’Avanzo, S. Schiff, P. Amodio, G. Sparacino (2008). Implementation of a wavelet-based procedure for eeg quantification during cognitive task, 13th International Symposium of the International Society on Hepatic Encephalopathy and Nitrogen Metabolism (ISHEN), 2008

8.      S.Schiff, E. Veronese E, G. Sparacino, G.M. Toffolo, P.Bisiacchi, A. Gatta, P. Amodio (2008). Mechanisms of P300 amplitude reduction in cirrhotic patients, 13th International Symposium of the International Society on Hepatic Encephalopathy and Nitrogen Metabolism (ISHEN), 2008

9.      G. Sparacino, C. D’Avanzo, E. Pasqualotto, E. Veronese, S.Schiff, P. Amodio. "Event Related Potentials Mesurement: A Bayesian Approach to Perform Improved Averaging and Single-Trial Estimation". In: Workshop Proceedings of SIMPAR 2008 Intl. Conf. on SIMULATION, MODELING and PROGRAMMING for AUTONOMOUS ROBOTS, Venice(Italy) 2008 November,3-4, ISBN 978-88-95872-01-8, pp. 389-394

10.   G. Sparacino, W. De Colle, D. De Luca, E. Arslan, Electroglottography and Microphone Signals Assessed by Approximate Entropy in Normal and Dysphonic Subjects, In Proceedings of the 6th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, Florence (Italy) 15-19 Decembre 2009, ISBN: 978-88-6453-094-9, pp.77-80

11.   Facchinetti A., Sparacino G., Vianello C., Cobelli C.. “Toward a Smart CGM Sensor: On-Line Algorithms for Calibration and Filtering”. Book of Abstracts, p. 3, 28th Workshop of the AIDPIT Study Group, 3rd European Diabetes Technology and Transplantation Meeting (EuDTT), Igls (Austria), January 25–27, 2009.

12.   Perez-Gandia C., Hernando E., Facchinetti A., Sparacino G., Cobelli C., Gomez E.. “A new Methodology to Compare Prediction Algorithms from Continuous Glucose Monitoring Data”. Book of abstracts, 2st International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Atene (Grecia), February 25–28, 2009.

13.   Facchinetti A., Sparacino G., Cappellotto P., Cobelli C.. “A new Extended Kalman Filtering Approach for the Calibration of Continuous Glucose Monitoring Sensors”. Book of abstracts, p. 146, 2st International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Atene (Grecia), February 25–28, 2009.

14.   Guerra S., Dalla Man C., Sparacino G., Renard E., and Cobelli C. The oral glucose minimal model in type 1 diabetes: an ingredient of DIAdvisorTM , , World Congress 2009 – Medical Physics and Biomedical Engineering, Munich, 7-12 Settembre 2009.

15.   Facchinetti A., Sparacino G., Kovatchev B., Cobelli C.. “Accuracy of CGM Sensors Improved in Real-Time by Exploiting Short-Time Prediction”. Book of Abstracts, p. A33, 9th Diabetes Technology Meeting (DTM), San Francisco (CA, USA), November 5–7, 2009.

16.   Facchinetti A., Sparacino G., Kovatchev B., Cobelli C.. “Real-Time Detection of CGM Sensor Failure”. Book of Abstracts, p. A34, 9th Diabetes Technology Meeting (DTM), San Francisco (CA, USA), November 5–7, 2009.

17.   Guerra S., Facchinetti A., Sparacino G., De Nicolao G., Cobelli C.. “Comparison of Four Methods for On-Line Calibration of CGM Data”. Book of Abstracts, p. A51, 9th Diabetes Technology Meeting (DTM), San Francisco (CA, USA),November 5–7, 2009.

18.   C. D’Avanzo, S. Schiff, E. Pasqualotto, P. Amodio, G. Sparacino. A Bayesian methodology to estimate single-trial ERPs with application to the study of the P300 variability in cirrhosis. In Proceedings of the World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany 2009

19.   A. Goljahani, C.D'Avanzo, V. Tarantino, P. Bisiacchi, G. Sparacino. Event-related EEG desynchronization and synchronization assessed during a time discrimination task. In Proceedings of the World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany 2009.

20.   Schiff S, D'Avanzo C, Cona G, Sparacino G, Bisiacchi P, Amodio P, Single-trial analysis explains reduction of P300 amplitude in cirrhotic patients. Psychophysiology: 46, S92, 2009.

21.   Tarantino V, Goljahani A, D'Avanzo C, Sparacino G, Bisiacchi P. Electrophysiological Correlates of Reference Memory in a Time Discrimination Task: An ERP and ERD/ERS Study. Psychophysiology: 46, S47, 2009

22.   Dalla Man C., Guerra S., Sparacino G., Renard E. and Cobelli C. "A Reduced type 1 Diabetes Model For Model Predictive Control", Book of abstracts, 3rd International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Basel (Switzerland), February 10–13, 2010

23.   Guerra S., Facchinetti A., Prendin A., Sparacino G., Cobelli C. “New Method for Recalibration of CGM Time-Series: Performance and Robustness Assessed by Simulation”, Book of abstracts, 3rd International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Basel (Switzerland), February 10–13, 2010.

24.   Guerra S., Facchinetti A., Schiavon M., Dalla Man C., Sparacino G. “A New Dynamic Risk Measure for Continuous Glucose Monitoring Time Series”. Book of abstracts, 3rd International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Basel (Switzerland), February 10–13, 2010.

25.   Facchinetti A., Trifoglio E., Sparacino G., Cobelli C. “Real-Time Self-Adaptive Prediction Algorithm for CGM Data Evaluated by Combining Different Indexes”, Book of abstracts, 3rd International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), Basel (Switzerland), February 10–13, 2010.

26.   Facchinetti A., Zecchin C., Sparacino G., Cobelli C. “Comparison of Different Neural Networks Structures for the Real-Time Prediction of Glucose Level”, Book of Abstract at 10th Diabetes Technology Meeting (DTM), Bethesda (MD, USA), November 11-13, 2010.

27.   Facchinetti A., Trifoglio E., Sparacino G., Cobelli C. “New Index to Optimally Design a CGM Glucose Prediction Algorithm”, Book of Abstract at 10th Diabetes Technology Meeting (DTM), Bethesda (MD, USA), November 11-13, 2010.

28.   Guerra S., Dalla Man C., Sparacino G., Renard E., Avogaro A., Maran A., Cobelli C. “Glucose Rate of Appearance and Plasma Insulin Concentration Models for Use in Prediction Algorithms” Book of Abstract at 10th Diabetes Technology Meeting (DTM), Bethesda (MD, USA), November 11-13, 2010.

29.   Mezzalana E., Bizzotto R., Sparacino G., Zamuner S. "Multinomial logistic functions in Markov-chain models for modeling sleep architecture: internal validation based on VPCs", PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe, ISBN/ISSN: 1871-6032, PAGE 19, Abstr 1893 [www.page-meeting.org/?abstract=1893], 2010.

30.   Schiff S, Goljahani A, D'Avanzo C, Parpaiola F, Amodio P, Sparacino G, Bisiacchi P, "Induced theta activity during event-based prospective memory task", in Proc. of the 3rd International Conference on Prospective Memory , Vancouver, Canada, July 2010.

31.   Facchinetti A, Del Favero S, Sparacino G, Cobelli C. Detecting failures of the glucose sensor-insulin pump system: Improved overnight safety monitoring for Type-1 diabetes. Conf Proc IEEE Eng Med Biol Soc. 2011 Aug;2011:4947-50.

32.   Zanon M, Riz M, Sparacino G, Facchinetti A, Suri RE, Talary MS, Cobelli C. Assessment of linear regression techniques for modeling multisensor data for non-invasive continuous glucose monitoring. Conf Proc IEEE Eng Med Biol Soc. 2011 Aug;2011:2538-41.

33.   Scarpa F, Brigadoi S, Cutini S, Scatturin P, Zorzi M, Dellracqua R, Sparacino G. A methodology to improve estimation of stimulus-evoked hemodynamic response from fNIRS measurements. Conf Proc IEEE Eng Med Biol Soc. 2011 Aug;2011:785-8.

34.   Zecchin C., Facchinetti A., Sparacino G., De Nicolao G., Cobelli C. “A new neural network approach for short-term glucose prediction using continuous glucose monitoring time-series and meal information”, Conf Proc IEEE Eng Med Biol Soc. 2011 Aug;2011:5653-6.

35.   Goljahani A., D'Avanzo C., Genna C., Silvoni S., Piccione F., Sparacino G. “Performance of a P300-based BCI system improved by a Bayesian single-trial ERP estimation technique”. Proceedings of the 5th International Brain-Computer Interface Conference 2011, Graz University of Technology, Austria, September 22-24, 2011, pp52-55, ISBN 978-3-85125-140-1.

36.   S. Brigadoi, F. Scarpa, S. Cutini, P. Scatturin, R. Dell’Acqua, G. Sparacino (2011) “Development of a new method to reduce global physiological trends in fNIRS measures of brain activation” . Brain'11 & BrainPET'11, Barcelona, Spain, May 25 ­ 28.

37.   Facchinetti A., Sparacino G., Calore F., Cobelli C. “On-Line CGM Denoising Improves Hypo/Hyperglycemic Alert Generation”. Book of abstracts, 4th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), London (UK), Feb 16–19, 2011.

38.   Facchinetti A., Zecchin C., Sparacino G., De Nicolao G., Cobelli C. “A New Neural Network Approach to Improve Effectiveness of Short-Term Glucose Prediction”. Book of abstracts, 4th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), London (UK), Feb 16–19, 2011.

39.   Guerra S., Sparacino G., Facchinetti A., Maran A., Cobelli C. “Dynamic Risk Space of CGM Time-Series: Assessment of Quality of Glucose Control”. Book of abstracts, 4th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), London (UK), Feb 16–19, 2011.

40.   Zanon M., Riz M., Facchinetti A., Sparacino G., Cobelli C., Suri R., Mueller M., De Feo O., Caduff A., Talary M. “Assessment of Linear Techniques to Model Multisensor Data for Non-Invasive Continuous Glucose Monitoring”. Book of abstracts, 4th International Conference on Advanced Technologies and Treatments for Diabetes (ATTD), London (UK), Feb 16–19, 2011.

41.   Facchinetti A., Del Favero S., Sparacino G., Cobelli C. “Improving Overnight Safety Monitoring in Type-1 Diabetic Subjects: a Method to Detect Failures of the Glucose Sensor-Insulin Pump System”. Book of abstracts, 11th Diabetes Technology Meeting (DTM), San Francisco (CA, USA), October 25-27, 2011.

42.   Guerra S. Zanon M., Maran A., Sparacino G., Cobelli C. "Parsimonious description of Glucose Variability investigated by a Sparse PCA Approach". Book of abstracts, 11th Diabetes Technology Meeting (DTM), San Francisco (CA, USA), October 25-27, 2011.

43.   F. Scarpa, C. Fabris, S. Brigadoi, S. Cutini, P. Scatturin, R. Dell'Acqua, G. Sparacino (2012). A GLM-Based Approach to Estimate Stimulus-Evoked Hemodynamic Response from fNIRS Measurements. Proc. 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), Shanghai, China, May 17 – 20, vol. 3, pp. 736-739, ISBN 978-1-61284-099-4

44.   S. Brigadoi, F. Scarpa, S. Cutini, P. Scatturin, R. Dell'Acqua, M. Zorzi, G. Sparacino (2012). Hemodynamic response estimation from fNIRS signal through a modeling approach exploiting the reference channel. Proc. 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), Shanghai, China, May 17 – 20, vol. 3, pp. 661-664, ISBN 978-1-61284-099-4

45.   Zecchin C., Facchinetti A., Sparacino G., Cobelli C.  Hypoglycemic alerts generated by short-time glucose prediction reduce time spent in hypo: in silico study Book of Abstracts International Conference on Advanced Technologies and Treatments for Diabetes 5th International Conference on Advanced Technologies and Treatments for Diabetes Feb 2012 Barcelona (Spain)    2012

46.   Zecchin C., Cherubin L., Facchinetti A., Sparacino G., Cobelli C. Jump neural network for short time prediction of glucose concentration using meal information in type 1 diabetes        . Book of Abstracts, 34th Annual International Conference of the IEEE-EMBS IEEE Engineering in Medicine and Biology Conference     San Diego (CA, USA) 2012

47.   Zecchin C., Facchinetti A., Sparacino G., Cobelli C.  Prediction-based alerting methods could reduce number and duration of hypoglycemic events: an in silico quantification Book of Abstracts of Diabetes Technology Meeting Diabetes Technology Meeting Bethesda (MD, USA)      2012

48.   Bhavaraju N.C., Cobelli C., Facchinetti A., Garcia A., Hampapuram H., Kamath A., Peyser T., Rack-Gomer A.L., Sparacino G., Zecchin C. Dexcom G4-AP: Advanced CGM for Artificial Pancreas Development. DIABETES TECHNOLOGY & THERAPEUTICS 15, A65, 2013

49.   Zecchin C., Facchinetti A., Manohar C., Kudva Y., Levine J., Basu A.,Sparacino G., Dalla Man C., Cobelli C. PHYSICAL ACTIVITY MEASURED BY PAMS VS. CGM TRENDS: CORRELATION ANALYSIS. DIABETES TECHNOLOGY & THERAPEUTICS 15 sup 1, A77, 2013

50.   Zanon M, Sparacino G, Facchinetti A, Talary MS, Caduff A, Cobelli C. EFFECTS OF SWEAT EVENTS ON THE CALIBRATION OF A MULTISENSOR DEVICE FOR NON-INVASIVE CONTINUOUS GLUCOSE MONITORING. DIABETES TECHNOLOGY & THERAPEUTICS 15, A77, 2013

51.   Kamath A, Bhavaraju NC, Cobelli C, Facchinetti A, Garcia A, Hampapuram H, Peyser T, Rack-Gomer AL, Sparacino G, Zecchin C DEXCOM G4-AP: ADVANCED CGM FOR ARTIFICIAL PANCREAS DEVELOPMENT. DIABETES TECHNOLOGY & THERAPEUTICS 15 sup 1, A 65, 2013

52.   Facchinetti A, Del Favero S, Castle J. R., Ward W. K., Sparacino G., Cobelli C. MODEL OF CGM ERROR FROM MULTIPLE SENSOR DATA: DISSECTION INTO PHYSIOLOGICAL AND TECHNOLOGICAL COMPONENTS. DIABETES TECHNOLOGY & THERAPEUTICS 15 Sup 1, A61, 2013

53.   Del Favero S, Facchinetti A, Sparacino G, Cobelli C  IMPROVING PATIENT OVERNIGHT SAFETY: GLUCOSE-SENSOR AND INSULIN-PUMPS FAILURES DETECTED EXPLOITING AN AVERAGE MODEL. DIABETES TECHNOLOGY & THERAPEUTICS 15 sup 1 A93, 2013

54.   Del Favero S, Facchinetti A, Sparacino G, Cobelli C  RETROFITTING ALGORITHM FOR A POSTERIORI ENHANCEMENT OF CGM TRACES BY BLOOD GLUCOSE REFERENCES. DIABETES TECHNOLOGY & THERAPEUTICS 15 Sup 1, A58, 2013

55.   Zecchin, C. Facchinetti, A. Sparacino, G. Cobelli, C. Neural network for prediction of glucose concentration in type 1 diabetic patients. Frontiers in Artificial Intelligence and Applications, 257: 303-306, 2013

56.   G. Sparacino, A. Facchinetti, C. Zecchin, C. Cobelli (2013). “Algorithmically Smart” Continuous Glucose Sensor Concept for Diabetes Monitoring. In: Proceedings of the XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. IFMBE PROCEEDINGS, vol. 41, p. 1543-1546, Springer International Publishing, ISBN: 9783319008462, ISSN: 1680-0737, Seville, Spain, September 25-28, 2013, doi: 10.1007/978-3-319-00846-2_381

57.   C. Fabris, A. S. Sejling, G. Sparacino, A. Goljahani, J. Duun-Henriksen, L. S. Remvig, C. Cobelli, C. B. Juhl (2013). Hypoglycaemia-Related EEG Changes Assessed by Approximate Entropy . In: IFMBE ProceedingsXIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. vol. 41, p. 686-689, ISBN: 9783319008455, Seville, Spain, September 25-29, 2013, doi: 10.1007/978-3-319-00846-2_170

58.   A. Goljahani, A. S. Sejling, G. Sparacino, C. Fabris, J. Duun-Henriksen, L. S. Remvig, C. Cobelli, C. B. Juhl (2013). Variability of EEG Theta Power Modulation in Type 1 Diabetics Increases during Hypo-glycaemia. In: IFMBE ProceedingsXIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. vol. 41, p. 539-542, ISBN: 9783319008455, Seville, Spain, September 25-29, 2013, doi: 10.1007/978-3-319-00846-2_133

59.   Fabris C, Facchinetti A, Sparacino G, Cobelli C. Sparse Principal Component Analysis for the parsimonious description of glucose variability in diabetes. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:6643-6. doi: 10.1109/EMBC.2014.6945151.

60.   Rubega M, Sparacino G, Sejling AS, Juhl CB, Cobelli C. Decrease of EEG Coherence during hypoglycemia in type 1 diabetic subjects. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:2375-8. doi: 10.1109/EMBC.2015.7318871.

61.   Vettoretti M, Facchinetti A, Sparacino G, Cobelli C.Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:2363-6. doi: 10.1109/EMBC.2015.7318868.

62.   Vettoretti M, Facchinetti A, Sparacino G, Cobelli C. Accuracy of devices for self-monitoring of blood glucose: A stochastic error model. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:2359-62. doi: 10.1109/EMBC.2015.7318867.

63.   Rubega M, Cecchetto C, Vassanelli S, Sparacino G.Automated analysis of local field potentials evoked by mechanical whisker stimulation in rat barrel cortex. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:1520-3. doi: 10.1109/EMBC.2015.7318660.

64.   Frigo, G., Brigadoi, S., Giorgi, G., Sparacino, G., Narduzzi, C. A compressive sensing spectral model for fNIRS haemodynamic response de-noising. Proceedings IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015, pp. 244-249, 2015

65.   Frigo, G., Rubega, M., Lezziero, G., (...), Sparacino, G., Bertocco, M. A software-based platform for multichannel electrophysiological data acquisition. Proceedings IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015, pp. 353-358, 2015.

 

 

 

 

INTERNATIONAL PATENTS

 

  1. Sparacino G., Facchinetti A., Cobelli C., Università di Padova. “Method and device for processing glycemia level data by means of self-adaptive filtering, predicting the future glycemia level and generating alerts”. (Identificativo: WO 2009/136372, International Publication Date: 12/11/2009).
  2. Facchinetti A., Guerra S., Sparacino G., De Nicolao G., Cobelli C.. “Method to Recalibrate Continuous Glucose Monitoring Data On-Line”. Provisional File (US provisional patent application No. 61/257,288). Publication date 02/11/2009.  Facchinetti A., Guerra S., Sparacino G., De Nicolao G., Cobelli C.. “Method to Recalibrate Continuous Glucose Monitoring Data On-Line”, International Patent Application PCT/IB2010/054947 at with the International Bureau of the World Intellectual Property Organisation, November 02, 2010.
  3. Guerra S., Facchinetti A., Sparacino G., Schiavon M., Cobelli C. (2011). Alert System for Hypo and Hyperglycemia Prevention based on Clinical Risk. US provisional patent application No. 61/551,773 , Università di Padova
  4. Facchinetti A., Del Favero S., Sparacino G., Cobelli C. (2012). Method to Improve Safety Monitoring in Type-1 Diabetic Patients by Detecting in Real-Time Failures of the Glucose Sensor-Insulin Pump System. US 61/606,549
  5. Bhavaraju NC, Hampapuram H, Kamath AU, Rack-Gomer AL, Cobelli C, Facchinetti A, Sparacino G, Zecchin C, SYSTEMS AND METHODS FOR PROVIDING SENSITIVE AND SPECIFIC ALARMS US 61/720,286, 2012
  6. Del Favero S., Facchinetti A., Sparacino G., Cobelli C. (2013). Retrospective retrofitting method to generate a continuous glucose concentration profile by exploiting continuous glucose monitoring sensor data and blood glucose. US 61/767,032
  7. Vettoretti, M., Facchinetti A., Sparacino G., Cobelli C (2015). Individualized multiple-day simulation model of type 1 diabetic patient decision-making for developing, testing and optimizing insulin therapies driven by glucose sensors” (Provisional patent application US Serial No. 62/163,091)
  8. Facchinetti A., Sparacino G., Cobelli C., Kovatchev B. (2015) Improved accuracy continuous glucose monitoring method, system, and device, PCT/US2015/045340