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Updated: May 2, 2026

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Home-Based Monitor for Gait and Activity Analysis
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使用可穿戴惯性传感器估计语音特征
Zuyu Du1, Yaodan Xu2, Xinsheng Yu3
1School of Information Science and Technology, ShanghaiTech University, Shanghai, China.
Journal of voice : official journal of the Voice Foundation
|October 11, 2024
概括
研究人员探索使用胸部振动来捕捉语音特征,发现胸骨加速有效地跟踪表情,声音和音调. 这表明了新的数字生物标志物的潜力,而无需对麦克风的隐私问题.
科学领域:
- 生物医学工程 生物医学工程
- 语音处理 语音处理
- 数字健康数字健康
背景情况:
- 语音特征是精神病和神经认知疾病的新兴数字生物标志物.
- 基于麦克风的语音录音面临着隐私泄露和环境噪音等局限性,阻碍了临床使用,特别是长期监测.
研究的目的:
- 为了研究从胸壁加速中提取语音特征的可行性.
- 评估胸骨加速作为麦克风的可行替代品,以捕捉语音特征.
主要方法:
- 十个健康的受试者在不同的速度和大声下执行了语言任务 (句子重复,阅读).
- 同时录制语音 (麦克风) 和胸部振动 (胸骨加速计).
- 从两种信号中提取和比较声学和时间相关的前音特征,使用线性匹配和相关性分析.
主要成果:
- 对于所有六个与时间相关的形特征,加速和麦克风特征之间发现了很高的一致性.
- 对19个 (任务1) 和17个 (任务2) 的声学特征观察到良好的一致性,主要与大声和音调有关.
- 胸骨加速有效地跟踪与时间相关的语音前奏,大声和音调.
结论:
- 从胸骨加速得出语音特征是可行的.
- 这种方法为开发数字生物标志物提供了一个有希望的,保护隐私的方法.
- 有潜在的应用存在于与体和大声语音特征相关的疾病.
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