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AMPRIMO, Gianluca

AMPRIMO, Gianluca  

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Titolo Data di pubblicazione Autore(i) File
Deep Learning for hand tracking in Parkinson’s Disease video-based assessment: Current and future perspectives 1-gen-2024 Amprimo, Gianluca; Masi, Giulia; Olmo, Gabriella; Ferraris, Claudia
Exergames as a rehabilitation tool to enhance the upper limbs functionality and performance in chronic stroke survivors: a preliminary study 1-gen-2024 Vismara, Luca; Ferraris, Claudia; Amprimo, Gianluca; Pettiti, Giuseppe; Buffone, Francesca; Tarantino, Andrea Gianmaria; Mauro, Alessandro; Priano, Lorenzo
Hand tracking for clinical applications: Validation of the Google MediaPipe Hand (GMH) and the depth-enhanced GMH-D frameworks 1-gen-2024 Amprimo, Gianluca; Masi, Giulia; Pettiti, Giuseppe; Olmo, Gabriella; Priano, Lorenzo; Ferraris, Claudia
Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states 1-gen-2024 Amprimo, Gianluca; Ferraris, Claudia
Computer Vision and Image Processing in Structural Health Monitoring: Overview of Recent Applications 1-gen-2023 Pettiti, Giuseppe; Ferraris, Claudia; Amprimo, Gianluca
Effects of Exergaming on motor performance in Parkinson's disease: a pilot study using Azure Kinect 1-gen-2023 Ferraris, Claudia; Amprimo, Gianluca; Pettiti, Giuseppe; Galli, Federica; Priano, Lorenzo; Mauro, Alessandro
Electrodermal Activity in the Evaluation of Engagement for Telemedicine Applications 1-gen-2023 G. Masi ; G. Amprimo ,; I. Rechichi ; C.Ferraris; L.Priano
Enhancing upper limb mobility through gamified tasks and Azure Kinect: a preliminary study in post-stroke subjects 1-gen-2023 Amprimo, Gianluca; Pettiti, Giuseppe; Ferraris, Claudia
Measuring Brain Activation Patterns from Raw Single-Channel EEG during Exergaming: A Pilot Study 1-gen-2023 Amprimo, Gianluca; Ferraris, Claudia
New Perspectives in Nonintrusive Sleep Monitoring for Neurodegenerative Diseases--A Narrative Review 1-gen-2023 Amprimo, Gianluca; Ferraris, Claudia
Stress and Workload Assessment in Aviation--A Narrative Review 1-gen-2023 Amprimo, Gianluca; Ferraris, Claudia
Assessment Tasks and Virtual Exergames for Remote Monitoring of Parkinson's Disease: An Integrated Approach Based on Azure Kinect 1-gen-2022 Amprimo G. ,; Masi G.; Priano L.,; Azzaro C.; Galli F. ; Pettiti G.; Mauro A.,; Ferraris C.
Assessment Tasks and Virtual Exergames for Remote Monitoring of Parkinson’s Disease: An Integrated Approach Based on Azure Kinect 1-gen-2022 Amprimo, Gianluca; Masi, Giulia; Priano, Lorenzo; Azzaro, Corrado; Galli, Federica; Pettiti, Giuseppe; Mauro, Alessandro; Ferraris, Claudia
Automatic Detector of Gait Alterations using RGB-D sensor and supervised classifiers: a preliminary study 1-gen-2022 Ferraris, C; Amprimo, G; Pettiti, G; Masi, G; Priano, L
Computation of Gait Parameters in Post Stroke and Parkinson's Disease: A Comparative Study Using RGB-D Sensors and Optoelectronic Systems 1-gen-2022 Cimolin V.; Vismara L.; Ferraris C.; Amprimo G.; Pettiti G.; Lopez R.; Galli M.; Cremascoli R.; Sinagra S.; Mauro A.; Priano L.
Kinect-Based Assessment of Lower Limbs during Gait in Post-Stroke Hemiplegic Patients: A Narrative Review 1-gen-2022 Cerfoglio S.; Ferraris C.; Vismara L.; Amprimo G.; Priano L.; Pettiti G.; Galli M.; Mauro A.; Cimolin V.
Telerehabilitation of cognitive, motor and sleep disorders in neurological pathologies: the REHOME project 1-gen-2022 Ferraris, C; Pettiti, G; Amprimo, G; Desideri, D; Pratola, P; Sacco, K; Ronga, I; Coppo, G; Soprani, D; Barbagallo, J; Antinoro, S; Ariano, P; Privitera, L
Usability of the REHOME Solution for the Telerehabilitation in Neurological Diseases: Preliminary Results on Motor and Cognitive Platforms 1-gen-2022 C. Ferraris ; I. Ronga ; R. Pratola; G. Coppo; T. Bosso ,; S. Falco ,; G. Amprimo ,; G. Pettiti ; S. Lo Priore; L. Priano,; A. Mauro,; D.Desideri
Kinect-based solution for the home monitoring of gait and balance in elderly people with and without neurological diseases 1-gen-2021 Gianluca Amprimo; Giuseppe Pettiti; Lorenzo Priano; Alessandro Mauro; Claudia Ferraris
Monitoring of gait parameters in post-stroke individuals: A feasibility study using rgb-d sensors 1-gen-2021 Ferraris C.; Cimolin V.; Vismara L.; Votta V.; Amprimo G.; Cremascoli R.; Galli M.; Nerino R.; Mauro A.; Priano L.