The functional connectivity between cortex and muscle during motor tasks can change after stroke. Motor rehabilitation aims at restoring it, either by re-establishing “close-to-normal” connectivity or supporting the development of alternative pathways. With the ultimate aim to design a rehabilitative approach based on a combination of Electroencephalographic (EEG) and Electromyographic (EMG) signals, we studied how different processing pipelines affect the extraction of a potential hybrid feature to discriminate movement tasks. Such feature will be employed in a novel hybrid Brain-Computer Interface system for motor-rehabilitation. In this setting, the control feature will be derived from a combined EEG and EMG connectivity pattern estimated online during upper limb movement attempts.

Towards a hybrid EEG-EMG feature for the classification of upper limb movements: comparison of different processing pipelines / de Seta, V.; Toppi, J.; Pichiorri, F.; Masciullo, M.; Colamarino, E.; Mattia, D.; Cincotti, F.. - (2021), pp. 355-358. (Intervento presentato al convegno 10th International IEEE EMBS Conference on Neural Engineering 2021 (NER2021) tenutosi a Virtuale) [10.1109/NER49283.2021.9441390].

Towards a hybrid EEG-EMG feature for the classification of upper limb movements: comparison of different processing pipelines

V. de Seta
;
J. Toppi;F. Pichiorri;E. Colamarino;D. Mattia;F. Cincotti
2021

Abstract

The functional connectivity between cortex and muscle during motor tasks can change after stroke. Motor rehabilitation aims at restoring it, either by re-establishing “close-to-normal” connectivity or supporting the development of alternative pathways. With the ultimate aim to design a rehabilitative approach based on a combination of Electroencephalographic (EEG) and Electromyographic (EMG) signals, we studied how different processing pipelines affect the extraction of a potential hybrid feature to discriminate movement tasks. Such feature will be employed in a novel hybrid Brain-Computer Interface system for motor-rehabilitation. In this setting, the control feature will be derived from a combined EEG and EMG connectivity pattern estimated online during upper limb movement attempts.
2021
10th International IEEE EMBS Conference on Neural Engineering 2021 (NER2021)
EEG; EMG; Cortico-Muscular Interactions; Hybrid Brain-Computer Interface
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Towards a hybrid EEG-EMG feature for the classification of upper limb movements: comparison of different processing pipelines / de Seta, V.; Toppi, J.; Pichiorri, F.; Masciullo, M.; Colamarino, E.; Mattia, D.; Cincotti, F.. - (2021), pp. 355-358. (Intervento presentato al convegno 10th International IEEE EMBS Conference on Neural Engineering 2021 (NER2021) tenutosi a Virtuale) [10.1109/NER49283.2021.9441390].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1492888
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