首个中文心衰语音数据库，验证了汉语发音可识别心衰状态。
A Chinese Heart Failure Status Speech Database with Universal and Personalised Classification
- 构建了心衰患者住院前后配对录音的中文语音数据库
- 个人化配对分类法比传统方法更准确，证明个体差异影响诊断
- 提出自适应频域滤波器分析语音频率重要性，适合语音医疗研究者
语音是一种低成本、无侵入性的数据源，可用于识别急性和慢性心力衰竭（HF）。然而，目前尚缺乏关于汉语音节是否包含心衰相关信号的研究，而这一现象在其他语言中已有充分验证。本研究首次构建了中国心衰患者语音数据库，包含住院前后的配对录音。结果表明，采用标准的‘患者级’与个性化的‘配对级’分类方法均能有效检测心衰，后者作为未来研究中去说话人依赖的基准。统计检验与分类结果表明，个体差异是导致误判的主要因素。此外，本文提出一种自适应频率滤波器（AFF），用于频率重要性分析。数据与演示已发布于 https://github.com/panyue1998/Voice_HF。
原文摘要 · Abstract (English)
Speech is a cost-effective and non-intrusive data source for identifying acute and chronic heart failure (HF). However, there is a lack of research on whether Chinese syllables contain HF-related information, as observed in other well-studied languages. This study presents the first Chinese speech database of HF patients, featuring paired recordings taken before and after hospitalisation. The findings confirm the effectiveness of the Chinese language in HF detection using both standard 'patient-wise' and personalised 'pair-wise' classification approaches, with the latter serving as an ideal speaker-decoupled baseline for future research. Statistical tests and classification results highlight individual differences as key contributors to inaccuracy. Additionally, an adaptive frequency filter (AFF) is proposed for frequency importance analysis. The data and demonstrations are published at https://github.com/panyue1998/Voice_HF.
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