在分娩过程中,语音交流和对疼痛的感知发声
Daria Valente1, Cecile Magnard2, Alexis Koutseff3
1Department of Life Sciences and Systems Biology, University of Turin, Torino 10123, Italy.
概括
人类发声中的非线性声学现象 (NLP),如分娩时的尖叫,信号强烈的疼痛. 听众根据这些粗,大声和高音调的声音准确地评估疼痛水平.
科学领域:
- 生物声学是一种生物声学.
- 人类沟通 人类沟通
- 疼痛感知 疼痛感知 疼痛感知
背景情况:
- 众所周知,非线性声学现象 (NLP) 在动物发声中发出痛苦信号.
- 在成年人语音交流中NLP的作用,特别是在表达疼痛方面,尚不清楚.
研究的目的:
- 研究人类自发非语言发音中的疼痛声学相关的产生和感知.
- 检查非线性声学现象如何促进分娩期间的疼痛沟通.
主要方法:
- 对妇女在分娩期间产生的自发发音的声学分析.
- 心理声学实验使用自然和合成的声音刺激与天真和专家的听众.
主要成果:
- 随着分娩的进展,发声表现出增加的粗度,基本频率,不稳定性,响度和持续时间,与自我评估的疼痛相关.
- 听众 (天真和专家) 给最后的分娩阶段的发声赋予了更高的疼痛评级.
- 感知实验证实,非线性现象是评估疼痛的关键线索.
结论:
- 非线性声学现象有效地传达人类强烈的,疼痛引起的痛苦.
- 这些发现与NLP在脊椎动物声信号中信号应急和唤醒的既定功能保持一致.
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