认知障碍或没有认知障碍的老年人自发言语的词汇语言特征:可靠性分析
Phillip Hamrick1, Victoria Sanborn2, Rachel Ostrand3
1Department of Psychological Sciences, Kent State University, Kent, OH, United States.
JMIR aging
|October 11, 2023
概括
语音分析显示,在老年人中,无论认知状态如何,词汇特征都是一致的. 这支持语音模式作为潜在的数字生物标志物,用于随着时间的推移监测认知健康.
科学领域:
- 老年学是指老年学的学科.
- 计算语言学 计算语言学
- 神经科学是一个神经科学.
背景情况:
- 语音分析为早期发现阿尔茨海默病提供了有希望的数字生物标志物.
- 很少有研究评估了老年人自发言语的一致性,以监测认知状态.
- 语音的词汇特征可以作为认知功能的可靠代理标记.
研究的目的:
- 调查认知障碍和没有认知障碍的老年人的词汇语言特征的一致性.
- 确定语音模式是否可以可靠地用于区分认知状态.
- 探索语音分析作为认知健康的数字生物标志物的潜力.
主要方法:
- 包括39名具有不同认知状态的老年人 (平均年龄为81.1岁).
- 利用图片描述和阐述任务来引起自发的言语.
- 使用Python和自然语言工具包进行自动语音功能计算.
主要成果:
- 词汇语音特性在认知障碍和完整群体 (r = 0.490.65) 的任务中表现出一致的可靠性.
- 词汇语言特征的个体内变异性通常被保留.
- 语音速率和填充率是认知完整组中最一致的指数,而语音速率在轻度认知障碍组中最一致.
结论:
- 自动计算的词汇语音属性在不同认知障碍水平的老年人中是一致的.
- 这些发现支持语音分析对随着时间的推移监测认知状态的有用性.
- 鼓励进一步研究语音分析和认知健康的数字生物标志物.
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