使用生物识别语音和咳声音特征识别COPD患者
Yasushi Obase1, Susumu Fukahori2, Jun Iriki3
1Department of Respiratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1, Sakamoto, Nagasaki, Nagasaki, 852-8501, Japan; Department of Respiratory Medicine, Nagasaki University Hospital, 1-7-1, Sakamoto, Nagasaki, Nagasaki, 852-8501, Japan.
Respiratory investigation
|December 13, 2025
概括
非侵入性语音分析显示了查慢性阻塞性肺病 (COPD) 的潜力. 虽然仅限于女性,但它在男性中达到80%以上的准确性,这表明它是一个有希望的,可访问的诊断工具.
科学领域:
- 呼吸系统医学 呼吸系统医学
- 生物医学工程 生物医学工程
- 声学分析 声学分析
背景情况:
- 慢性阻塞性肺病 (COPD) 是一个重要的全球健康问题,由于认识不足,经常被诊断不足.
- 症状的延迟识别有助于COPD的低诊断.
- 这项研究研究了非侵入性语音和咳声音分析用于COPD识别的潜力.
研究的目的:
- 评估使用语音和咳声音分析用于非侵入性COPD查的可行性.
- 为了确定声学特征在识别COPD的诊断性能.
- 探索基于智能手机的录音对COPD评估的有用性.
主要方法:
- 55名参与者 (26名COPD,29名对照) 的前性研究.
- 使用特征提取和选择对语音和咳声音进行声学分析.
- 后勤回归分类与四重交叉验证.
主要成果:
- 自音音 /u/ 显示有区分能力,但在混合性别队列中,整体表现低于80%.
- 在男性参与者中,准确度超过了80%,这表明歧视力更高.
- 智能手机记录显示精度与专用设备相比较;临床数据没有提高分类.
结论:
- 语音分析提供了一个潜在的COPD非侵入性查方法.
- 目前的研究结果受限于对男性参与者的关注,并且可能不适用于所有性别或相关的呼吸道疾病.
- 未来的研究应该包括多样化的群体和其他呼吸系统疾病,如支气管病.
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