Inclusive mobile brain-body imaging achieves equivalent EEG data quality across racial groups

Electroencephalography (EEG) research systematically excludes participants with textured hair, limiting generalizability. While inclusive hardware offers a solution, it remains unvalidated in dynamic settings. This study bridges this ecological gap by determining if equitable data quality is achievable across racial groups during a complex Mobile Brain/Body Imaging (MoBI) paradigm. We recruited 17 older adults from racially and ethnically underrepresented groups (REUG) and 17 age-and-sex-matched White older adults. Participants completed an auditory oddball task while sitting and during active standing. EEG was recorded using a dry-brush-electrode system paired with culturally sensitive procedures. The primary outcome was event-related potential (ERP) data quality, quantified using the Standardized Measurement Error (SME) for P3 amplitude and latency. Total data loss was comparable between White (8.29%) and REUG participants (9.88%), with no group differences (p = 0.91) or group×condition interactions (p = 0.82). We found no significant main effects of group or group-by-condition interactions on any SME measure (all p > 0.05), and equivalence testing confirmed that SME for P3 amplitude and latency was statistically equivalent in 16 of 18 stimulus × postural comparisons. A sensitivity analysis restricting the REUG group to participants with textured hair (REUG-T, n = 9) yielded a near-identical pattern (15 of 18 comparisons). Signal‑to‑noise ratio at Fz for frequent stimuli increased from sitting to standing (F = 10.33, p = 0.002, adjusted p = 0.036). Behavioral performance was similar across groups. This study provides the first evidence that equitable ERP data quality is achievable across racial groups during active MoBI by combining inclusive hardware with culturally sensitive protocols. These findings confirm that the technological incompatibility underlying historical underrepresentation is surmountable when paired with culturally sensitive protocols, enabling more inclusive and generalizable cognitive neuroscience.Author summary: Electroencephalography (EEG) is a vital tool for monitoring brain health, yet standard sensors often fail to record reliable data from individuals with coarse or curly hair. This technological limitation has led to the systematic exclusion of Black participants and others with textured hair from neuroscientific research. In this study, we investigated whether utilizing a specific dry-brush electrode system, paired with culturally sensitive research protocols, could bridge this gap. We compared brain data quality between older adults from racially underrepresented groups and matched White participants during a cognitive task performed while sitting and standing. We found that this inclusive approach produced data of statistically equivalent quality across racial groups, even during the more physically demanding standing condition. Also, total data loss was comparable between White (8.29%) and underrepresented participants (9.88%). This finding is critical because it demonstrates that the historical lack of diversity in EEG research is a solvable problem. By validating that existing inclusive hardware works effectively in dynamic settings, we provide a roadmap for researchers to conduct more equitable studies, ensuring that future brain health innovations benefit all populations equally.