Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Luca Ascari"'
Autor:
Giovanni M. Di Liberto, Michele Barsotti, Giovanni Vecchiato, Jonas Ambeck-Madsen, Maria Del Vecchio, Pietro Avanzini, Luca Ascari
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract Driving a car requires high cognitive demands, from sustained attention to perception and action planning. Recent research investigated the neural processes reflecting the planning of driving actions, aiming to better understand the factors
Externí odkaz:
https://doaj.org/article/b7e47f480297433ebec372b376623c96
Autor:
Marianna Capecci, Rossella Cima, Filippo A. Barbini, Alice Mantoan, Francesca Sernissi, Stefano Lai, Riccardo Fava, Luca Tagliapietra, Luca Ascari, Roberto N. Izzo, Maria Eleonora Leombruni, Paola Casoli, Margherita Hibel, Maria Gabriella Ceravolo
Publikováno v:
Sensors, Vol 23, Iss 16, p 7238 (2023)
Background: “Ricominciare” is a single-center, prospective, pre-/post-intervention pilot study aimed at verifying the feasibility and safety of the ARC Intellicare (ARC) system (an artificial intelligence-powered and inertial motion unit-based mo
Externí odkaz:
https://doaj.org/article/bf6f1f50a0334f4c84c6e79cd6cfbe17
Autor:
Luca Ascari, Anna Marchenkova, Andrea Bellotti, Stefano Lai, Lucia Moro, Konstantin Koshmak, Alice Mantoan, Michele Barsotti, Raffaello Brondi, Giovanni Avveduto, Davide Sechi, Alberto Compagno, Pietro Avanzini, Jonas Ambeck-Madsen, Giovanni Vecchiato
Publikováno v:
Sensors, Vol 21, Iss 24, p 8167 (2021)
Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solu
Externí odkaz:
https://doaj.org/article/17f6fe5988e44c80b7ce45707dea00d0
Publikováno v:
Bioengineering, Vol 8, Iss 2, p 21 (2021)
Decoding motor intentions from non-invasive brain activity monitoring is one of the most challenging aspects in the Brain Computer Interface (BCI) field. This is especially true in online settings, where classification must be performed in real-time,
Externí odkaz:
https://doaj.org/article/ccb7967cede1451491ee4593f7d41ecb
Publikováno v:
Sensors, Vol 13, Iss 6, Pp 7735-7755 (2013)
Human motion monitoring and analysis can be an essential part of a wide spectrum of applications, including physical rehabilitation among other potential areas of interest. Creating non-invasive systems for monitoring patients while performing rehabi
Externí odkaz:
https://doaj.org/article/23ff9e5f5c7640c7a5d4346bbf718416
Autor:
Pietro Avanzini, Giovanni Vecchiato, Maria Del Vecchio, Giovanni M. Di Liberto, Luca Ascari, Michele Barsotti, Jonas Ambeck-Madsen
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports
Scientific Reports
Driving a car requires high cognitive demands, from sustained attention to perception and action planning. Recent research investigated the neural processes reflecting the planning of driving actions, aiming to better understand the factors leading t
Understanding mental processes in complex human behaviour is a key issue in the context of driving, representing a milestone for developing user-centred assistive driving devices. Here we propose a hybrid method based on electroencephalographic (EEG)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b097e00b4d36badc9a70c641e2f58fe
https://doi.org/10.1101/2021.09.16.460615
https://doi.org/10.1101/2021.09.16.460615
Publikováno v:
Cognitive neurodynamics. 16(5)
Understanding mental processes in complex human behavior is a key issue in driving, representing a milestone for developing user-centered assistive driving devices. Here, we propose a hybrid method based on electroencephalographic (EEG) and electromy
Autor:
Maria Del Vecchio, Pietro Avanzini, Sergey Antopolskiy, Luca Ascari, Giacomo Rizzolatti, Luca Kubin, Giovanni Vecchiato, Fabio Deon, Jonas Ambeck-Madsen
Publikováno v:
Brain Research. 1716:16-26
The objective of the present work was to identify electroencephalographic (EEG) components in order to distinguish between braking and accelerating intention in simulated car driving. To do so, we collected high-density EEG data from thirty participa
Publikováno v:
Bioengineering
Volume 8
Issue 2
Bioengineering, Vol 8, Iss 21, p 21 (2021)
Volume 8
Issue 2
Bioengineering, Vol 8, Iss 21, p 21 (2021)
Decoding motor intentions from non-invasive brain activity monitoring is one of the most challenging aspects in the Brain Computer Interface (BCI) field. This is especially true in online settings, where classification must be performed in real-time,