Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Fabio Rizzoglio"'
Publikováno v:
eLife, Vol 12 (2023)
Existing intracortical brain computer interfaces (iBCIs) transform neural activity into control signals capable of restoring movement to persons with paralysis. However, the accuracy of the ‘decoder’ at the heart of the iBCI typically degrades ov
Externí odkaz:
https://doaj.org/article/714421f780af4f45b104933ace899fa6
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 11 (2023)
In the past, linear dimensionality-reduction techniques, such as Principal Component Analysis, have been used to simplify the myoelectric control of high-dimensional prosthetic hands. Nonetheless, their nonlinear counterparts, such as Autoencoders, h
Externí odkaz:
https://doaj.org/article/61b35240700f4fd89cc1ab695d230732
Autor:
Alexandra A. Portnova-Fahreeva, Fabio Rizzoglio, Maura Casadio, Ferdinando A. Mussa-Ivaldi, Eric Rombokas
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 11 (2023)
Dimensionality reduction techniques have proven useful in simplifying complex hand kinematics. They may allow for a low-dimensional kinematic or myoelectric interface to be used to control a high-dimensional hand. Controlling a high-dimensional hand,
Externí odkaz:
https://doaj.org/article/b953586f5a8246cea410705f262db14a
Autor:
Alexandra A. Portnova-Fahreeva, Fabio Rizzoglio, Ilana Nisky, Maura Casadio, Ferdinando A. Mussa-Ivaldi, Eric Rombokas
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 8 (2020)
The purpose of this study was to find a parsimonious representation of hand kinematics data that could facilitate prosthetic hand control. Principal Component Analysis (PCA) and a non-linear Autoencoder Network (nAEN) were compared in their effective
Externí odkaz:
https://doaj.org/article/e1baf688028a4c0aaf4610a924fbde02
Publikováno v:
IEEE Transactions on Biomedical Engineering. :1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3271c68f1300831df372994828354e9
https://doi.org/10.1109/tbme.2023.3237081
https://doi.org/10.1109/tbme.2023.3237081
Autor:
Fabio Rizzoglio, Ege Altan, Xuan Ma, Kevin L. Bodkin, Brian M. Dekleva, Sara A. Solla, Ann Kennedy, Lee E. Miller
Intracortical brain-computer interfaces (iBCIs) enable paralyzed persons to generate movement, but current methods require large amounts of both neural and movement-related data to be collected from the iBCI user for supervised decoder training. We h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a50cad36012cec04adf8fbddc0f42085
https://doi.org/10.1101/2022.11.12.515040
https://doi.org/10.1101/2022.11.12.515040
Existing intracortical brain computer interfaces (iBCIs) transform neural activity into control signals capable of restoring movement to persons with paralysis. However, the accuracy of the “decoder” at the heart of the iBCI typically degrades ov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3996246c83d32a671c8cdb4ff6bb1b80
https://doi.org/10.1101/2022.08.26.504777
https://doi.org/10.1101/2022.08.26.504777
Autor:
Maura Casadio, Giulia Ballardini, Marco Giordano, Ferdinando A. Mussa-Ivaldi, Fabio Rizzoglio
Publikováno v:
Biosystems & Biorobotics ISBN: 9783030703158
Controlling an assistive robotic manipulator can play a crucial role in improving lives of individuals with motor impairments. Here, we propose the use of state-of-the-art machine learning techniques for dimensionality reduction—non-linear autoenco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::028d43d5d962b1cc51d70fa766e92990
https://doi.org/10.1007/978-3-030-70316-5_110
https://doi.org/10.1007/978-3-030-70316-5_110
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687892
ICPR Workshops (2)
ICPR Workshops (2)
Regaining functional independence plays a crucial role to improve the qualify of life of individuals with motor disabilities. Here, we address this problem within the framework of Body-Machine Interfaces (BoMIs). BoMIs enable individuals with restric
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c6d3d33032442b8b5dae6beae707a265
https://doi.org/10.1007/978-3-030-68790-8_19
https://doi.org/10.1007/978-3-030-68790-8_19
Autor:
Fabio Rizzoglio, Camilla Pierella, Ferdinando A. Mussa-Ivaldi, Dalia De Santis, Maura Casadio
Publikováno v:
Journal of Neural Engineering
Objective. Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::164cce508aedb399d69b94d27fda4d6f