Synchronization of EEG and sEMG Events: Towards a Framework for Sequential and Causal Analysis in Stroke Patients

Stroke rehabilitation is a complex process that requires continuous monitoring using several techniques, each with its own limitations. Clinical scales such as the Fugl-Meyer Assessment, primarily rely on the observer-dependent scoring, which can lead to variability in results. The joint analysis of biomedical signals such as electroencephalography (EEG) and surface electromyography (sEMG), recorded simultaneously, presents challenges to obtain robust conclusions about their relationship due, among other factors, to the lack of joint temporal references in which events occur and uncontrolled confounding variables. To address these limitations, a protocol is proposed that develops encoding methodologies considering the sequential nature of multiple and synchronized signals of physiological data using precise time references that indicate when the events of interest take place. Our results show that such protocol and associated devices produce accurate temporal references for the joint assessment of the EEG and sEMG signals, and the corresponding causal sequential characterization.