Implementation of mobile EEG for resting-state and visual evoked potentials in young children in rural Ethiopia.

Children living in low- and middle-income countries (LMIC) are at disproportionately higher risk of neurodevelopmental delays due to exposure to adverse biological and environmental hazards. In infancy, global developmental assessments, such as the Bayley Scales, are insensitive, do not strongly correlate with later cognitive outcomes, and require adaptation for different populations and cultural contexts. Electroencephalography (EEG) objectively measures electrical brain activity and may provide early neural markers predictive of long-term cognitive outcomes. The visual evoked potential (VEP) interrogates the efficiency of visual cortical processing and reflects neural processing speed. Mobile EEG enables the assessment of neural processing in settings where such technologies were historically inaccessible. This paper describes the experiences and lessons learned from implementing mobile EEG and VEP in rural Amhara, Ethiopia as part of the Longitudinal Infant Growth and Development (LIDG) study (NCT06296238). We describe adaptations and strategies to address and optimize data capture (e.g., dry electrode tips to improve scalp contact, tailored protocols, and adequate equipment specifications), environmental challenges (e.g., space constraints, lack of water supply, power outage) and cultural factors (e.g., hair type) unique to the study setting and population. Our formative research underscored the importance of creating awareness among community members (e.g., mothers, fathers, and religious leaders) and local clinicians to improve community engagement and buy-in. Culturally sensitive child behavior management techniques were also critical to ensure EEG completion and high data quality. With community sensitization, we had high consent rates for EEG/VEP (>90%). We completed EEG recordings within an average ± standard deviation of 20 ± 11 minutes. After data processing, approximately 90% and 70% of participants met predefined data quality thresholds for resting EEG and VEP, respectively. Implementing mobile EEG/VEP was feasible and acceptable in rural Ethiopia, with a relatively high proportion of recordings meeting quality standards.