Rehabilitation and Neural Engineering Laboratory

Elvira Pirondini, PhD

  • Research Assistant Professor

Elvira Pirondini, PhD, obtained her M.Sc. degree in Bioengineering from EPFL, Lausanne, in 2012. During this time, she was awarded a fellowship from the Bertarelli Program in Translational Neuroscience and Neuroengineering to carry out her M.Sc. thesis at Harvard Medical School. She then earned her PhD in 2017 at the Swiss Federal Institute of Technology (EPFL), Lausanne, where she was honored with the 2017 Outstanding PhD thesis Distinction in Electrical Engineering. Her thesis focused on robotic rehabilitation for stroke patients and brain imaging. During her PhD, she was the recipient of the Brown Institute for Brain Science Scholar fellowship to conduct part of her training in the department of Neuroscience at Brown University.
Dr. Pirondini conducted her post-doctoral training at the University of Geneva, Switzerland, and at the Defitech Center for Interventional Neurotherapies of the CHUV hospital in Lausanne, Switzerland. She worked in parallel with human patients and animal models of stroke. Specifically, she worked on the development of a new model of subcortical stroke in primates to understand the neural mechanisms of recovery. She completed these explorations using electroencephalography (EEG) and functional magnetic resonance imaging  (fMRI) in humans to study restoration mechanisms in stroke patients.

Research Interest Summary

Stroke, motor control, proprioception, functional magnetic resonance imaging (fMRI), electroencephalography (EEG), biomarkers

Research Interests

Dr. Pirondini primary research interests include the study of upper limb motor control strategies in humans and animal models, and neuroimaging tools for the design of innovative clinical approaches for rehabilitation in neural disorders. Specifically, she is interested on understanding neural and structural changes after stroke and correlating them with motor and proprioceptive impairments. For this, she combines robotic devices and advance signal processing techniques.