TaghiBeyglou Behrad, Kaufman Jaycee, Fossat Yan
Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
KITE Research Institute, Toronto Rehabilitation Institute- University Health Network, Toronto, ON, Canada.
Digit Biomark. 2025 Jun 24;9(1):130-139. doi: 10.1159/000547077. eCollection 2025 Jan-Dec.
Hypertension is the leading risk factor for cardiovascular disorders. Early detection and initiation of treatment have been identified as the most effective ways to reduce the burden of hypertension. The most common method for detecting hypertension is blood pressure measurement, typically performed with cuff-based devices, where systolic pressure (SBP) and diastolic pressure (DBP) are measured through Korotkoff sounds. Although this method is accurate and non-invasive, it requires technical expertise and is often inaccessible in rural and remote areas. In this study, we investigated the feasibility of using overt speech (random speech corpora) through multiple short recordings for hypertension screening based on two hypertension guidelines: (1) SBP ≥135 mm Hg OR DBP ≥85 mm Hg, and (2) SBP ≥140 mm Hg OR DBP ≥90 mm Hg.
We incorporated speech recordings from 573 participants (197 women) with diverse ages and body mass index and extracted temporal, spectral, and nonlinear acoustic features through three different frameworks, all of which are based on classical and boosted machine learning models. The models were evaluated using a leave-one-subject-out cross-validation scheme.
Our proposed pipeline achieved a balanced accuracy (BACC) of 61% for males and 70% for females under the relaxed criterion (SBP ≥135 OR DBP ≥85), and a BACC of 71% for males and 78% for females under the stricter European Society of Hypertension (ESH) guidelines (SBP ≥140 OR DBP ≥90).
These results demonstrate the potential of employing overt speech alongside acoustic analysis for hypertension screening.
高血压是心血管疾病的主要危险因素。早期检测和开始治疗已被确定为减轻高血压负担的最有效方法。检测高血压最常见的方法是测量血压，通常使用基于袖带的设备进行，通过柯氏音测量收缩压（SBP）和舒张压（DBP）。虽然这种方法准确且无创，但它需要专业技术，并且在农村和偏远地区往往无法实现。在本研究中，我们根据两项高血压指南，研究了通过多次短录音使用公开语音（随机语音语料库）进行高血压筛查的可行性：（1）SBP≥135mmHg或DBP≥85mmHg，以及（2）SBP≥140mmHg或DBP≥90mmHg。
我们纳入了573名参与者（197名女性）的语音记录，这些参与者年龄和体重指数各不相同，并通过三种不同的框架提取了时间、频谱和非线性声学特征，所有这些框架均基于经典和增强机器学习模型。使用留一法交叉验证方案对模型进行评估。
在宽松标准（SBP≥135或DBP≥85）下，我们提出的流程男性的平衡准确率（BACC）为61%，女性为70%；在更严格的欧洲高血压学会（ESH）指南（SBP≥140或DBP≥90）下，男性的BACC为71%，女性为78%。
这些结果证明了将公开语音与声学分析一起用于高血压筛查的潜力。
