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Emma Colamarino

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Implementing physiologically-based approaches to improve Brain-Computer Interfaces usability in post-stroke motor rehabilitation on 2019-02-26
An All-in-One BCI-Supported Motor Imagery Training Station: Validation in a Real Clinical Setting with Chronic Stroke Patients on Converging Clinical and Engineering Research on Neurorehabilitation III. Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018), October 16-20, 2018, Pisa, Italy 2019
Bipolar filters improve usability of Brain-Computer Interface technology in post-stroke motor rehabilitation on Converging Clinical and Engineering Research on Neurorehabilitation III. Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018), October 16 – 20, 2018, Pisa, Italy 2019
Brain-computer interface technology for upper limb rehabilitation after stroke: a translational effort on EUROPEAN JOURNAL OF NEUROLOGYAbstracts of the 4th Congress of the European academy of neurology 2018
Semiautomatic physiologically-driven feature selection improves the usability of a brain computer interface system in post-stroke motor rehabilitation on Abstract Book of the Seventh International Brain-Computer Interface Meeting 2018
GUIDER: a GUI for semiautomatic, physiologically driven EEG feature selection for a rehabilitation BCI on Proceedings of the 7th Graz Brain-Computer Interface Conference 2017. From Vision to Reality 2017
Neurophysiological constraints of control parameters for a brain computer interface system to support post-stroke motor rehabilitation on 2017 School and Symposium on Advanced Neurorehabilitation (SSNR2017). Proceedings 2017

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