Hybrid Brain-Computer Interfaces (hBCI) integrate brain and muscle signals to enhance motor rehabilitation of stroke survivors, by closing the loop between the lesioned brain and the paretic limb. To date, little attention has been devoted to their potential efficacy in managing the maladaptive movement patterns that afflict post-stroke motor outcome (unwanted abnormal co-contrations, spasticity). This study proposes a comparison of Cortico-Muscular Coherence (CMC) patterns assessed in stroke patients before and after a 1-month rehabilitation intervention based on a hBCI-controlled Functional Electrical Stimulation (FES) treatment, which included a module to monitor non-physiological movement patterns. Results demonstrated the efficacy of this type of assistive technology for post-stroke rehabilitation, addressing patient-tailored interventions able to reduce the maladaptive mechanisms.

Hybrid Brain Computer Interface-Based Rehabilitation Addressing Post-Stroke Maladaptive Movement Patterns / Toppi, Jlenia; Savina, Giulia; Colamarino, Emma; De Seta, Valeria; Patarini, Francesca; Cincotti, Febo; Pichiorri, Floriana; Mattia, Donatella. - (2025), pp. 431-436. ( 19th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR 2025) Chicago, IL, USA ) [10.1109/ICORR66766.2025.11062988].

Hybrid Brain Computer Interface-Based Rehabilitation Addressing Post-Stroke Maladaptive Movement Patterns

Toppi Jlenia
;
Savina Giulia;Colamarino Emma;de Seta Valeria;Patarini Francesca;Cincotti Febo;
2025

Abstract

Hybrid Brain-Computer Interfaces (hBCI) integrate brain and muscle signals to enhance motor rehabilitation of stroke survivors, by closing the loop between the lesioned brain and the paretic limb. To date, little attention has been devoted to their potential efficacy in managing the maladaptive movement patterns that afflict post-stroke motor outcome (unwanted abnormal co-contrations, spasticity). This study proposes a comparison of Cortico-Muscular Coherence (CMC) patterns assessed in stroke patients before and after a 1-month rehabilitation intervention based on a hBCI-controlled Functional Electrical Stimulation (FES) treatment, which included a module to monitor non-physiological movement patterns. Results demonstrated the efficacy of this type of assistive technology for post-stroke rehabilitation, addressing patient-tailored interventions able to reduce the maladaptive mechanisms.
2025
19th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR 2025)
hBCI; CMC; FES; stroke; Adult; Aged; Brain-Computer Interfaces; Electromyography; Female; Humans; Male; Middle Aged; Movement; Stroke; Stroke Rehabilitation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Hybrid Brain Computer Interface-Based Rehabilitation Addressing Post-Stroke Maladaptive Movement Patterns / Toppi, Jlenia; Savina, Giulia; Colamarino, Emma; De Seta, Valeria; Patarini, Francesca; Cincotti, Febo; Pichiorri, Floriana; Mattia, Donatella. - (2025), pp. 431-436. ( 19th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR 2025) Chicago, IL, USA ) [10.1109/ICORR66766.2025.11062988].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1743303
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