使用声学分析和机器学习对随机语音样本进行高血压查:可行性研究
Behrad TaghiBeyglou1,2,3, Jaycee Kaufman3, Yan Fossat3,4
1Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
这项研究探讨了使用语音分析进行高血压查,为传统血压手套提供了一个潜在的可访问的替代方案. 该方法显示出有希望的准确性,特别是对于女性来说,在识别患有心压和心压升高的个体方面.
科学领域:
- 心脏病学 心脏病学
- 生物医学工程 生物医学工程
- 语音处理 语音处理
背景情况:
- 高血压是心血管疾病的主要危险因素.
- 早期检测和治疗对于管理高血压至关重要.
- 基于手的血压测量虽然准确,但在偏远地区面临着可访问性挑战.
研究的目的:
- 调查使用公开言论用于高血压查的可行性.
- 评估语音分析作为传统血压监测的可访问替代方案.
主要方法:
- 收集了来自573名参与者的演讲录音.
- 使用机器学习模型提取声学特征 (时间,光谱,非线性).
- 通过交叉验证 (leave-one-subject-out) 评估模型性能.
主要成果:
- 在宽松的高血压标准下 (SBP ≥135 或 DBP ≥85) 达到61% (男性) 和70% (女性) 的平衡精度 (BACC).
- 根据更严格的ESH指南 (SBP ≥140 或 DBP ≥90) 达到71%的BACC (男性) 和78% (女性).
结论:
- 露面语音分析显示了对高血压查的潜力.
- 这种声学方法可以提高对高血压检测的可访问性.
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