Marianna Semprini, PhD
Affiliations: | Robotics, Brain and Cognitive Sciences | Italian Institute of Technology, Genoa, United States |
Area:
Brain-Machine InterfaceGoogle:
"Marianna Semprini"Mean distance: 15.59 (cluster 22) | S | N | B | C | P |
Parents
Sign in to add mentor| Ferdinando A. Mussa-Ivaldi | grad student | Northwestern | |
| Alessandro Vato | grad student | 2008-2011 | IIT |
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Publications
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| Lotti N, Missiroli F, Galofaro E, et al. (2023) Soft Robotics to Enhance Upper Limb Endurance in Individuals with Multiple Sclerosis. Soft Robotics |
| Bonassi G, Semprini M, Mandich P, et al. (2023) Neural oscillations modulation during working memory in pre-manifest and early Huntington's disease. Brain Research. 148540 |
| Marinelli A, Boccardo N, Canepa M, et al. (2023) A Novel Method for Vibrotactile Proprioceptive Feedback Using Spatial Encoding and Gaussian Interpolation. Ieee Transactions On Bio-Medical Engineering. 70: 3354-3365 |
| Semprini M, Lencioni T, Hinterlang W, et al. (2022) User-centered design and development of TWIN-Acta: A novel control suite of the TWIN lower limb exoskeleton for the rehabilitation of persons post-stroke. Frontiers in Neuroscience. 16: 915707 |
| Chiappalone M, Semprini M. (2022) Using robots to advance clinical translation in neurorehabilitation. Science Robotics. 7: eabo1966 |
| Carè M, Averna A, Barban F, et al. (2022) The impact of closed-loop intracortical stimulation on neural activity in brain-injured, anesthetized animals. Bioelectronic Medicine. 8: 4 |
| Garro F, Chiappalone M, Buccelli S, et al. (2021) Neuromechanical Biomarkers for Robotic Neurorehabilitation. Frontiers in Neurorobotics. 15: 742163 |
| Barban F, Chiappalone M, Bonassi G, et al. (2021) Yet another artefact rejection study: an exploration of cleaning methods for biological and neuromodulatory noise. Journal of Neural Engineering. 18 |
| Iandolo R, Semprini M, Sona D, et al. (2021) Investigating the spectral features of the brain meso-scale structure at rest. Human Brain Mapping |
| Iandolo R, Semprini M, Buccelli S, et al. (2020) Small-World Propensity Reveals the Frequency Specificity of Resting State Networks. Ieee Open Journal of Engineering in Medicine and Biology. 1: 57-64 |