用临床和计算测量语音和语言障碍的临床和计算措施来描述和检测妄想症
Sunny X Tang1, Yan Cong1, Gwenyth Mercep1
1From the Institute of Behavioral Science, Feinstein Institutes for Medical Research, Northwell Health, Glen Oaks, New York (Tang, Cong, Serpe, Berretta, John); the Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York (Mercep, Bhatti, Gromova, Sinvani); Department of Linguistics, University of Pennsylvania, Philadelphia, PA (Liberman).
这项研究表明,分析语音和语言模式可以帮助老年人检测痴呆症. 对这些特征的计算分析提高了诊断准确度,提供了一种有前途的非侵入性方法.
科学领域:
- 老年医学 老年医学
- 计算语言学 计算语言学
- 认知神经学 认知神经学
背景情况:
- 痴呆症是住院老年人常见但诊断不足的疾病,其特点是精神状态发生变化.
- 现有的妄想检测方法对言语和语言障碍的关注有限.
- 这项研究探讨了语音和语言特征在妄想检测中的作用.
研究的目的:
- 描述与妄想相关的言语和语言障碍.
- 为使用计算语音和语言特征来检测妄想提供概念证明.
主要方法:
- 住院的老年人接受了妄想评估和语言任务.
- 语音和语言障碍使用临床尺度进行了评分.
- 自动管道提取了声学和文本特征;机器学习模型预测了妄想状态.
主要成果:
- 与对照组相比,患有妄想症的患者表现出更高的总语言障碍和不连贯性,以及较低的类别流利性.
- 认知功能障碍与增加的语言障碍和流利性降低相关.
- 结合计算语言功能,改善了妄想预测的准确度,达到78%.
结论:
- 在妄患者中,语言障碍升高可能表明下值认知障碍.
- 计算式语音和语言特征显示出潜在的准确,非侵入性和高效的妄想生物标志物.
- 需要对更大的样本大小进行进一步的研究,以获得可泛化的检测模型.
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