On sound-based interpretation of neonatal EEG

TL;DR

This paper introduces a novel sound-based method for neonatal EEG interpretation using FM/AM modulation, aiming to enable quick and intuitive differentiation of healthy and abnormal brain activity, and compares it with existing algorithms through expert surveys.

Contribution

It presents a new FM/AM-based sonification method for neonatal EEG analysis and evaluates its effectiveness against phase vocoder algorithms and visual interpretation.

Findings

Sound-based methods perform similarly well in detecting neonatal seizures.

Both methods show less variability than visual interpretation.

Auditory perception of frequency evolution influences detection sensitivity.

Abstract

Significant training is required to visually interpret neonatal EEG signals. This study explores alternative sound-based methods for EEG interpretation which are designed to allow for intuitive and quick differentiation between healthy background activity and abnormal activity such as seizures. A novel method based on frequency and amplitude modulation (FM/AM) is presented. The algorithm is tuned to facilitate the audio domain perception of rhythmic activity which is specific to neonatal seizures. The method is compared with the previously developed phase vocoder algorithm for different time compressing factors. A survey is conducted amongst a cohort of non-EEG experts to quantitatively and qualitatively examine the performance of sound-based methods in comparison with the visual interpretation. It is shown that both sonification methods perform similarly well, with a smaller inter-observer variability in comparison with visual. A post-survey analysis of results is performed by examining the sensitivity of the ear to frequency evolution in audio.