Scholarlink

<p>We aimed to investigate the frequency, changes, and chaotic correlation dimensions of fetal facial expression videos using artificial intelligence (AI) and speculate the state of the fetal brain activity. We applied our original AI for classifying fetal facial expressions to 57,208 frames, total of 95.27&#xa0;min, from 47singleton pregnancies at 28 to 37 weeks of gestation, obtained at Miyake Clinic between December 2023 and February 2024 at 0.1-second intervals. Time, transitions and correlation dimensions of the facial expressions were investigated. There was a significant difference between expressions. Neutral and mouthing showed significantly longer durations; 71.0, 9.4–174.8 (Mean, 5–95%ile) and 53.3, 0.7–127.3&#xa0;s for neutral and mouthing, respectively. The longest transitions were neutral to mouthing at 2,237.5&#xa0;s. The median correlation dimensions for before, during, and after neutral and mouthing were 1.14, 1.22, and 1.23, and 1.07, 1.15, and 1.24, respectively. Analyzing fetal facial expression videos using AI may raise the possibility of being able to indirectly quantify brain activity. The ability to infer fetal brain activity via fetal facial expressions both qualitatively and quantitatively might be considered to have significant biological implications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Characteristics of fetal facial expression changes using artificial intelligence: a pilot study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月28日

查看全文
  • Yasunari Miyagi,
  • Toshiyuki Hata,
  • Takahito Miyake

摘要

We aimed to investigate the frequency, changes, and chaotic correlation dimensions of fetal facial expression videos using artificial intelligence (AI) and speculate the state of the fetal brain activity. We applied our original AI for classifying fetal facial expressions to 57,208 frames, total of 95.27 min, from 47singleton pregnancies at 28 to 37 weeks of gestation, obtained at Miyake Clinic between December 2023 and February 2024 at 0.1-second intervals. Time, transitions and correlation dimensions of the facial expressions were investigated. There was a significant difference between expressions. Neutral and mouthing showed significantly longer durations; 71.0, 9.4–174.8 (Mean, 5–95%ile) and 53.3, 0.7–127.3 s for neutral and mouthing, respectively. The longest transitions were neutral to mouthing at 2,237.5 s. The median correlation dimensions for before, during, and after neutral and mouthing were 1.14, 1.22, and 1.23, and 1.07, 1.15, and 1.24, respectively. Analyzing fetal facial expression videos using AI may raise the possibility of being able to indirectly quantify brain activity. The ability to infer fetal brain activity via fetal facial expressions both qualitatively and quantitatively might be considered to have significant biological implications.