A New Compound-Limbs Paradigm: Integrating Upper-Limb Swing Improves Lower-Limb Stepping Intention Decoding From EEG.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Brain-computer interface (BCI) systems utilizing electroencephalography (EEG) aim to enable voluntary control of lower-extremity powered exoskeletons.
• Existing EEG-BCI paradigms often overlook the natural coordination between upper and lower limbs during walking, leading to unnatural control schemes.

Purpose of the Study:

• To propose and validate a novel stepping-matched human EEG-BCI paradigm incorporating compound-limbs movement (unilateral lower and contralateral upper limbs).
• To assess the feasibility of this paradigm for decoding human stepping intentions for natural control of walking assistance devices.

Main Methods:

• Development of a compound-limbs EEG-BCI paradigm involving simultaneous lower and upper limb actions.
• Application of Common Spatial Pattern (CSP) algorithms, including subject-specific CSP (SSCSP) and filter-bank CSP (FBCSP), for feature extraction.
• Experimental validation under motor execution (ME) and motor imagery (MI) conditions.

Main Results:

• The proposed compound-limbs EEG-BCI paradigm demonstrated feasibility in decoding stepping intentions.
• Subject-specific CSP (SSCSP) yielded the best classification accuracies: 89.02% ± 12.84% for ME and 73.70% ± 12.47% for MI.
• While slightly lower than single-upper-limb control, compound-limbs control significantly outperformed single-lower-limb control (by 24.30% in ME and 11.02% in MI).

Conclusions:

• The developed compound-limbs EEG-BCI paradigm is a viable approach for interpreting human stepping intentions.
• This paradigm offers a promising pathway towards achieving more natural and intuitive control of walking assistance devices.