Artificial intelligence to understand fluctuation of fetal brain activity by recognizing facial expressions.

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Abstract

To examine whether artificial intelligence can achieve discoveries regarding fetal brain activity.In this observational study, we collected images of fetal faces using a four-dimensional ultrasound technique obtained from singleton pregnancies of outpatients in routine practice at 27-37 weeks of gestation between February 1 and December 31, 2021. We developed an AI classifier to recognize seven facial expressions of fetuses, then applied it to video files of fetal facial images to generate the probabilities, as confidence scores, of each expression category. We used discrete Fourier transform and chaotic analysis to investigate the scores. The Mann-Whitney test, t-test, variance test, and one-way analysis of variance were used for statistical analysis.Facial expression changes were observed in cycles averaging 66-73 seconds. The power spectrum showed that mouthing and neutral expressions were the most prevalent. There was a difference between categories for the spectrum (p=0.004). We discovered two different states – dense and sparse – of confidence scores. The correlation dimension was 1.19±0.22 and 1.33±0.27 for dense and sparse, respectively (p=0.047).This method objectively and quantitatively demonstrated fetal brain activity and may provide insight into how the fetus spends its time in utero.This article is protected by copyright. All rights reserved.