Seuraa
Giovanni D'Addio
Giovanni D'Addio
Resp. Servizio di Bioingegneria, Fondazione Maugeri IRCCS, Istituto di Telese Terme
Vahvistettu sähköpostiosoite verkkotunnuksessa fsm.it
Nimike
Viittaukset
Viittaukset
Vuosi
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
1672007
An integrated approach based on uniform quantization for the evaluation of complexity of short-term heart period variability: application to 24h Holter recordings in healthy …
A Porta, L Faes, M Masé, G D’addio, GD Pinna, R Maestri, N Montano, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 17 (1), 2007
1472007
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, 133-140, 2016
872016
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
702019
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
692009
Machine learning to predict mortality after rehabilitation among patients with severe stroke
D Scrutinio, C Ricciardi, L Donisi, E Losavio, P Battista, P Guida, ...
Scientific reports 10 (1), 20127, 2020
592020
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 13, 114, 2020
572020
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
522004
An application of symbolic dynamics for FHRV assessment.
M Cesarelli, M Romano, P Bifulco, G Improta, G D'Addio
MIE, 123-127, 2012
512012
Work-related risk assessment according to the revised NIOSH lifting equation: A preliminary study using a wearable inertial sensor and machine learning
L Donisi, G Cesarelli, A Coccia, M Panigazzi, EM Capodaglio, G D’Addio
Sensors 21 (8), 2593, 2021
502021
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
XV Mediterranean Conference on Medical and Biological Engineering and …, 2020
472020
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
461998
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
422014
Classifying different stages of Parkinson’s disease through random forests
C Ricciardi, M Amboni, C De Santis, G Ricciardelli, G Improta, ...
XV Mediterranean Conference on Medical and Biological Engineering and …, 2020
412020
Agreement between opal and G-walk wearable inertial systems in gait analysis on normal and pathological subjects
G D’Addio, L Donisi, G Pagano, G Improta, A Biancardi, M Cesarelli
2019 41st Annual International Conference of the IEEE Engineering in …, 2019
412019
Design and validation of an e-textile-based wearable sock for remote gait and postural assessment
F Amitrano, A Coccia, C Ricciardi, L Donisi, G Cesarelli, EM Capodaglio, ...
Sensors 20 (22), 6691, 2020
392020
Prognostic decision support using symbolic dynamics in CTG monitoring.
M Cesarelli, M Romano, P Bifulco, G Improta, G D'Addio
EFMI-STC 186, 140-144, 2013
392013
Machine learning can detect the presence of Mild cognitive impairment in patients affected by Parkinson’s Disease
C Ricciardi, M Amboni, C De Santis, G Ricciardelli, G Improta, G D’Addio, ...
2020 IEEE International Symposium on Medical Measurements and Applications …, 2020
382020
Feasibility of machine learning in predicting features related to congenital nystagmus
G D’Addio, C Ricciardi, G Improta, P Bifulco, M Cesarelli
XV Mediterranean Conference on Medical and Biological Engineering and …, 2020
372020
Benchmarking between two wearable inertial systems for gait analysis based on a different sensor placement using several statistical approaches
L Donisi, G Pagano, G Cesarelli, A Coccia, F Amitrano, G D'Addio
Measurement 173, 108642, 2021
362021
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Artikkelit 1–20