Year: 2026
Type: article
Abstract: Background and Objectives: Sensorimotor rhythms (SMR) and their modulation are widely used in brain–computer interface (BCI) applications, but their reliable detection during overt upper-limb movements remains chal lenging due to motion-related artifacts and concurrent peripheral activity. This study investigates whether SMR modulation can be decoded during el bow flexion/extension performed under active and resistive conditions, with and without voluntary modulation. Methods: Nine healthy participants performed elbow flexion and ex tension across four run types: active (A), active with voluntary modulation (AM), resistive (R), and resistive with voluntary modulation (RM). Elec troencephalography (EEG), electromyography (EMG), and inertial measure ment unit (IMU) signals were synchronously acquired. EEG data were clas sified using a filter bank common spatial pattern (FBCSP)-based pipeline. EMG was analyzed to estimate the exerted force. Subjective workload was assessed using the NASA-TLX questionnaire. Statistical testing was con ducted to evaluate effects across experimental conditions. Results: Classification accuracies consistently exceeded chance level, with average values above (73 ± 14)% across participants and above (80 ± 12)% when discriminating SMR modulation regardless of movement type (A vs AM, R vs RM). EMG confirmed greater force output in resistive condi tions, while voluntary modulation was associated with increased muscular activation in most participants. Statistical testing highlighted effects mainly related to resistive conditions. In participants without significant force differ ences, classification remained above 70%, and event-related desynchroniza tion/synchronization analyses revealed distinct cortical modulations in the µ and β bands, supporting a neural origin of the decoded features. Workload ratings indicated higher cognitive demand during voluntary modulation and increased physical effort in resistive conditions, while combining resistance and voluntary modulation did not substantially increase perceived cognitive demand. Conclusions: The proposed framework enables detection of SMR modu lation during overt upper-limb movement, supporting rehabilitation scenarios in which movement resistance can be adaptively modulated based on real time neural activity.
Source: Machines
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7171487372