Giovanni D'Addio
Giovanni D'Addio
Resp. Servizio di Bioingegneria, Fondazione Maugeri IRCCS, Istituto di Telese Terme
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Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value
R Maestri, GD Pinna, A Accardo, P Allegrini, R Balocchi, G D'ADDIO, ...
Journal of cardiovascular electrophysiology 18 (4), 425-433, 2007
An integrated approach based on uniform quantization for the evaluation of complexity of short-term heart period variability: Application to Holter recordings in …
A Porta, L Faes, M Masé, G D’addio, GD Pinna, R Maestri, N Montano, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 17 (1), 015117, 2007
Assessment of cardiovascular regulation through irreversibility analysis of heart period variability: a 24 hours Holter study in healthy and chronic heart failure populations
A Porta, G D'addio, T Bassani, R Maestri, GD Pinna
Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2009
Dietary protein intake in sarcopenic obese older women
E Muscariello, G Nasti, M Siervo, M Di Maro, D Lapi, G D’Addio, ...
Clinical interventions in aging 11, 133, 2016
Using gait analysis’ parameters to classify Parkinsonism: A data mining approach
C Ricciardi, M Amboni, C De Santis, G Improta, G Volpe, L Iuppariello, ...
Computer methods and programs in biomedicine 180, 105033, 2019
Testing the presence of non stationarities in short heart rate variability series
A Porta, G D'addio, S Guzzetti, D Lucini, M Pagani
Computers in Cardiology, 2004, 645-648, 2004
Reproducibility of short-and long-term poincare plot parameters compared with frequency-domain HRV indexes in congestive heart failure
G D'addio, D Acanfora, GD Pinna, R Maestri, G Furgi, C Picone, F Rengo
Computers in Cardiology 1998. Vol. 25 (Cat. No. 98CH36292), 381-384, 1998
Feasibility of machine learning in predicting features related to congenital nystagmus
G D’Addio, C Ricciardi, G Improta, P Bifulco, M Cesarelli
Mediterranean Conference on Medical and Biological Engineering and Computing …, 2019
Efficacy of machine learning in predicting the kind of delivery by cardiotocography
G Improta, C Ricciardi, F Amato, G D’Addio, M Cesarelli, M Romano
Mediterranean conference on medical and biological engineering and computing …, 2019
An application of symbolic dynamics for FHRV assessment.
M Cesarelli, M Romano, P Bifulco, G Improta, G D'Addio
MIE, 123-127, 2012
In-time prognosis based on swarm intelligence for home-care monitoring: A case study on pulmonary disease
P Arpaia, C Manna, G Montenero, G D'Addio
IEEE Sensors Journal 12 (3), 692-698, 2011
Symbolic dynamic and frequency analysis in foetal monitoring
M Romano, G D'Addio, F Clemente, AM Ponsiglione, G Improta, ...
2014 IEEE International Symposium on Medical Measurements and Applications …, 2014
A piezoresistive array armband with reduced number of sensors for hand gesture recognition
D Esposito, E Andreozzi, GD Gargiulo, A Fratini, G D’Addio, GR Naik, ...
Frontiers in Neurorobotics, 114, 2020
Heart rate variability and drawing impairment in hypoxemic COPD
RA Incalzi, A Corsonello, L Trojano, C Pedone, D Acanfora, A Spada, ...
Brain and cognition 70 (1), 163-170, 2009
Comparison between clinical and instrumental assessing using Wii Fit system on balance control
G D'Addio, L Iuppariello, F Gallo, P Bifulco, M Cesarelli, B Lanzillo
2014 IEEE International Symposium on Medical Measurements and Applications …, 2014
Relationship between fractal dimension and power-law exponent of heart rate variability in normal and heart failure subjects
M Cusenza, A Accardo, G D'Addio, G Corbi
2010 Computing in Cardiology, 935-938, 2010
Clinical correlates of non-linear indices of heart rate variability in chronic heart failure patients
R Maestri, GD Pinna, R Balocchi, G D'Addio, M Ferrario, A Porta, R Sassi, ...
Walter de Gruyter 51 (4), 220-223, 2006
Symbolic analysis of 24h Holter heart period variability series: comparison between normal and heart failure patients
A Porta, G D'Addio, GD Pinna, R Maestri, T Gnecchi-Ruscone, R Furlan, ...
Computers in Cardiology, 2005, 575-578, 2005
Prognostic decision support using symbolic dynamics in CTG monitoring.
M Cesarelli, M Romano, P Bifulco, G Improta, G D'Addio
EFMI-STC, 140-144, 2013
Fractal behaviour of heart rate variability reflects severity in stroke patients
G D'Addio, G Corbi, A Accardo, G Russo, N Ferrara, MC Mazzoleni, ...
Medical Informatics in a United and Healthy Europe, 794-798, 2009
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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