An objective method to evaluate Neonatal Auditory pathways and index Auditory Cognition using the Cortical Auditory Evoked Potential (CAEP) and the Mismatch Negativity (MMN) Event-Related Potential (ERP)

Congenital hearing loss affects approximately 1–3 per 1,000 live births worldwide, with higher prevalence in many developing countries. Early identification supports speech, language, and cognitive development. Conventional neonatal screening uses auditory brainstem response (ABR) and otoacoustic emissions (OAE) to evaluate peripheral auditory function and brainstem pathways but does not directly assess cortical sound processing or auditory discrimination. Conventional electrophysiological assessments also involve individual scalp electrode placement and specialist interpretation, increasing preparation time and dependence on trained personnel.

This project developed a portable, wearable headband with integrated acquisition hardware and automated signal processing to evaluate auditory pathways and early sound processing in neonates. The platform targets three electrophysiological responses: ABR, cortical auditory evoked potentials (CAEP), and mismatch negativity (MMN). ABR assesses auditory brainstem responses while CAEP provides evidence of cortical responses to sound. MMN reflects the detection of changes in an auditory sequence and serves as an indicator of early auditory discrimination. By combining a customised neonatal headband with automated signal extraction, the system aims to simplify electrode positioning, reduce analysis time, and support objective assessment. With clinical validation, this approach could complement existing hearing screening by enabling broader evaluation of neonatal auditory function and identifying infants who require additional assessment and follow-up.

Publications:

Rathin K. Joshi, Manu K. S., Hari R. S., Ajay Krishnan A, M. Jayachandra, Manjunath Dandinarasaiah, Hardik J. Pandya, “Automated ABR and MMN extraction using a customized headband for hearing screening,” Biomedical Signal Processing and Control, Volume 94, 106264, 2024. DOI: https://doi.org/10.1016/j.bspc.2024.106264