帕金森病中的语音分析 - 一个系统的文献综述
Daniela Xavier1, Virginie Felizardo2, Beatriz Ferreira3
1Universidade da Beira Interior, Covilhã, Portugal.
Artificial intelligence in medicine
|March 25, 2025
概括
对帕金森病 (PD) 的早期诊断至关重要. 本综述表明,用机器学习进行语音分析可以有效地诊断和预测PD,提供了一个有前途的非侵入性方法.
科学领域:
- 神经学 神经学
- 生物医学工程 生物医学工程
- 语音科学 语言科学
背景情况:
- 帕金森病 (PD) 是一种神经退行性疾病,经常被诊断为晚期,限制了治疗疗效.
- 早期诊断和预后对于更好的疾病管理至关重要.
- 声音和语音变化是PD的早期标志.
研究的目的:
- 使用语音和语音分析系统审查用于诊断和预测帕金森病的机器学习模型.
- 在最近的文献中识别这些模型的当前趋势和性能.
主要方法:
- 对2019年至2023年间发表的研究进行系统性文献综述.
- 在ScienceDirect,IEEE Xplore和ACM图书馆数据库中进行的搜索.
- 纳入和排除标准适用于106项符合条件的研究.
主要成果:
- 大多数审查的研究 (94.34%) 专注于帕金森病的诊断.
- 一小部分研究 (11.32%) 涉及疾病预后.
- 机器学习模型在基于语音的PD检测中表现出高性能.
结论:
- 基于机器学习的语音分析是诊断和预测帕金森病的可行和有效方法.
- 经过审查的文献支持使用语音评估作为PD管理的非侵入性工具.
- 进一步的研究可以完善这些模型用于临床应用.
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