PDMS Microchannel Regenerative Peripheral Nerve Interface

Publications associées (27)

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Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Stefano Moia

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Real-time actuation of a dielectric elastomer actuator neuroprosthesis for facial paralysis

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Stefania Maria Aliki Konstantinidi, Armando Matthieu Walter, Amine Benouhiba

Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his mimic musculature on one or both sides of his face. This condition compromises the patient's communication and facial expressions, and thus dramatically reduce ...

2023

Improved Physiochemical Properties of Chitosan@PCL Nerve Conduits by Natural Molecule Crosslinking

Silvestro Micera

Nerve conduits may represent a valuable alternative to autograft for the regeneration of long-gap damages. However, no NCs have currently reached market approval for the regeneration of limiting gap lesions, which still represents the very bottleneck of th ...

MDPI2023

Reconstruction of nerve functional topography using recruitment curves enables selective electrical stimulation

Silvestro Micera, Simone Romeni, Bianca Ziliotto

Multi-polar stimulation protocols have been used in the past to increase the selectivity of electrical stimulation of the nervous system. Nonetheless, the number of possible multipolar stimulation protocols is prohibitively large and cannot be explored dur ...

IEEE2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Luca Pierantoni, Gabriele Marino

Computational models have been widely employed to study the electrical stimulation of the nervous system. Still, most applications either study fundamental mechanisms underlying stimulation, or address qualitative scientific questions. When quantitative qu ...

IEEE2023

Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has ...

Company Biologists Ltd2023

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Auke Ijspeert, Mohamed Bouri, Ali Reza Manzoori, Andrea Di Russo, Sara Messara

Exoskeletons intended for partial assistance of walking should be able to follow the gait pattern of their users, via online adaptive control strategies rather than imposing predefined kinetic or kinematic profiles. NeuroMuscular Controllers (NMCs) are ada ...

2023

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Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Stefano Moia

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Company Biologists Ltd2023

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Auke Ijspeert, Mohamed Bouri, Ali Reza Manzoori, Andrea Di Russo, Sara Messara

2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Luca Pierantoni, Gabriele Marino

IEEE2023