Evidence map›Paper›PMID 42566476›Full record

ArticlePLOS digital health2026

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

Sodiq Fakorede, Ke Liao, KathleenMae Rogers, Kai Cheng, Lydia Pemberton, Laura E Martin, Hannes Devos

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sodiq FakoredeDepartment of Physical Therapy, Rehabilitation Science, and Athletic Training, University of Kansas Medical Center, Kansas City, Kansas, United States of America.ORCID https://orcid.org/0000-0001-7717-105X
Ke LiaoHoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, United States of America.
KathleenMae RogersDepartment of Physical Therapy, Rehabilitation Science, and Athletic Training, University of Kansas Medical Center, Kansas City, Kansas, United States of America.
Kai ChengDepartment of Physical Therapy, Rehabilitation Science, and Athletic Training, University of Kansas Medical Center, Kansas City, Kansas, United States of America.
Lydia PembertonDepartment of Physical Therapy, Rehabilitation Science, and Athletic Training, University of Kansas Medical Center, Kansas City, Kansas, United States of America.
Laura E MartinHoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, United States of America.
Hannes DevosDepartment of Physical Therapy, Rehabilitation Science, and Athletic Training, University of Kansas Medical Center, Kansas City, Kansas, United States of America.ORCID https://orcid.org/0000-0002-8853-6840

Funding

University of Kansas Alzheimer's Disease Research Center (KU ADRC)P30AG072973 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI JONATHAN D MAHNKEN · 2021 to 2026
$25.3M
Kansas University Training Program in Neurological and Rehabilitation SciencesT32HD057850 · NICHD · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Jacob J. Sosnoff · 2009 to 2026
$3.4M
Enhancing Geroscience Scholarship and Faculty Development to Minimize Frailty and Maximize HealthspanK07AG060266 · NIA · UNIVERSITY OF KANSAS MEDICAL CENTER · PI TROEN, BRUCE R. · 2019 to 2023
$774k
NIA NIH HHS K07 AG060266NIA NIH HHS P30 AG072973NICHD NIH HHS T32 HD057850
6 · The paper itself

Abstract

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.

Identifiers

PMID42566476
PMCPMC13450788

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.