Claudio Gabbiani

Claudio Gabbiani is a PhD Researcher in Singapore-ETH Centre in 'Biomarkers for the assessment of upper limb sensorimotor impairments post-stroke'.

The research purpose is to develop and validate new tools for quantifying short-term and long-term rehabilitation outcomes, for example via specifically designed wearables, instrumented objects and technology-aided assessments.
Such approaches strongly rely on computational models that are able to process multi-modal data and eventually predict sensorimotor recovery.
Technological-aided assessments rely on RELab devices such as the ETH MIKE, the Virtual Peg Insertion Test (VPIT), and the ZurichMove wearable sensors.

Claudio completed his B.Sc. (2014) and M.Sc. (2017) degree in Biomedical Engineering in Politecnico di Torino (Turin, Italy) and then completed a 2nd level Master in Machine Learning and Big Data in Univeristà di Padova remotely in 2020/2021.
Claudio's passion are machine learning into the medical context, biomedical signal process and neurorehabilitation.

He has been a Biomedical Research Assistant at École Polytechnique Fédérale de Lausanne (Lausanne, Switzerland) in 2019 working on Mobile Brain/Body Imaging and analyzing the involvement of the brain during robotic assisted gait training on a treadmill (Lokomat) by using high-density EEG, EMG and force-measurements.