探索II型糖尿病对语音质量的影响
M A Saghiri1,2, Julia Vakhnovetsky3,4,5, Mahsa Amanabi4
1Biomaterial and Prosthodontics Laboratory, Department of Restorative Dentistry, Rutgers School of Dental Medicine, Rutgers Biomedical and Health Sciences, MSB C639A, 185 South Orange Avenue, Newark, NJ, 07103, USA. saghiri@gmail.com.
概括
语音分析可以帮助预先查II型糖尿病 (T2DM). 在T2DM患者和非糖尿病患者之间发现了显著的声音差异,特别是闪.
科学领域:
- 生物医学工程 生物医学工程
- 语音科学 语言科学
- 内分泌学 在内分泌学.
背景情况:
- 二型糖尿病 (T2DM) 是一个日益严重的全球健康问题.
- 早期发现和治疗T2DM对于预防并发症至关重要.
- 对于有效的T2DM查,需要使用非侵入性诊断工具.
研究的目的:
- 评估语音分析作为T2DM非侵入性预选工具的有效性.
- 确定特定的声学声音特征,区分T2DM和没有T2DM的个体.
- 探索语音特征与糖尿病状况之间的相关性.
主要方法:
- 一项涉及伊朗60名参与者 (30名T2DM,30名非糖尿病人) 的横截面研究.
- 使用WhatsApp收集语音录音,用于语音诱导任务.
- 使用Prat软件提取和分析了七个声学特征 (基本频率,动,闪,HNR,CPP,VOT,formant).
主要成果:
- 在T2DM和非糖尿病组之间观察到基本频率,动,闪,CPP和HNR的显著差异 (p <0.05).
- 闪光成为识别T2DM群体的最重要的预测因素.
- 在Cepstral峰值突出度 (CPP) 中,糖尿病状况和年龄之间的显著相互作用被注意到.
结论:
- 与非糖尿病人相比,患有T2DM的个体表现出明显的声音变化.
- 语音分析显示出作为T2DM成本效益和可访问的预选方法的潜力.
- 需要进一步的研究来验证这些发现在更大,更多样化的群体中.
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