在自发言语中的语言标记:对主观认知衰退的见解 (评论)
Sofia Segkouli1, Mara Gkioka2, Stylianos Kokkas1
1Centre for Research and Technology Hellas, Information Technologies Institute (CERTH/ITI), 57001 Thessaloniki, Greece.
Healthcare (Basel, Switzerland)
|November 27, 2025
概括
分析自发言语可以检测健康老年人的早期记忆衰退,为主动认知健康评估和识别主观记忆衰退 (SMD) 提供可扩展,非侵入性的工具.
科学领域:
- 神经科学是一个神经科学.
- 语言学的语言学.
- 老年学是一门学科.
背景情况:
- 全球人口增长和人口变化正在增加神经退行性疾病的发病率,如痴呆症和轻度认知障碍 (MCI).
- 主观记忆力下降 (SMD) 标志着正常认知的个体自我认知的认知能力下降,可能是MCI之前的.
- 语言障碍是神经退行性疾病和老年人早期记忆丧失的关键指标.
研究的目的:
- 审查来自自发和叙事演讲的语言特征,作为与阿尔茨海默病 (AD) 病理学相关的早期认知变化的敏感指标.
- 确定分析自发言语的方法,以检测健康老年人的早期记忆力下降.
主要方法:
- 根据PRISMA指南进行了系统审查.
- 包括分析SMD或粉样性病理患者自发言语的研究,报告语言表现指标.
- 专注于与参与者展示SMD或认知投诉没有客观损害的研究,在过去五年内以英语出版.
主要成果:
- 自发语音分析揭示了微妙的语言和认知变化,表明早期的AD病理.
- 声学和时间语音参数,包括沉默持续时间和语音段频率,是敏感的标记.
- 这些语音特征可以在健康的老年人中识别早期记忆力下降.
结论:
- 自发语音分析提供了一种有价值的非侵入性方法,用于检测早期的认知变化和记忆衰退.
- 声学和时间语音参数为与神经退行相关的微妙语言转变提供了洞察力.
- 自发语音表现代表了一个可扩展的,具有成本效益的诊断工具,用于主动的认知健康监测.
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