Wang Liangqi, Tian Shuo, Zhu Rong
State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, 100084 Beijing, China.
Microsyst Nanoeng. 2023 Sep 21;9:117. doi: 10.1038/s41378-023-00590-4. eCollection 2023.
Hypertension is a worldwide health problem and a primary risk factor for cardiovascular disease. Continuous monitoring of blood pressure has important clinical value for the early diagnosis and prevention of cardiovascular disease. However, existing technologies for wearable continuous blood pressure monitoring are usually inaccurate, rely on subject-specific calibration and have poor generalization across individuals, which limit their practical applications. Here, we report a new blood pressure measurement method and develop an associated wearable device to implement continuous blood pressure monitoring for new subjects. The wearable device detects cardiac output and pulse waveform features through dual photoplethysmography (PPG) sensors worn on the palmar and dorsal sides of the wrist, incorporating custom-made interface sensors to detect the wearing contact pressure and skin temperature. The detected multichannel signals are fused using a machine-learning algorithm to estimate continuous blood pressure in real time. This dual PPG sensing method effectively eliminates the personal differences in PPG signals caused by different people and different wearing conditions. The proposed wearable device enables continuous blood pressure monitoring with good generalizability across individuals and demonstrates promising potential in personal health care applications.
高血压是一个全球性的健康问题,也是心血管疾病的主要风险因素。持续监测血压对心血管疾病的早期诊断和预防具有重要的临床价值。然而,现有的可穿戴式连续血压监测技术通常不准确,依赖于个体特异性校准,且个体间的通用性较差,这限制了它们的实际应用。在此,我们报告一种新的血压测量方法,并开发一种相关的可穿戴设备,以对新受试者进行连续血压监测。该可穿戴设备通过佩戴在手腕掌侧和背侧的双光电容积脉搏波描记法(PPG)传感器检测心输出量和脉搏波形特征,并结合定制的接口传感器来检测佩戴接触压力和皮肤温度。利用机器学习算法对检测到的多通道信号进行融合,以实时估计连续血压。这种双PPG传感方法有效地消除了不同人和不同佩戴条件导致的PPG信号中的个体差异。所提出的可穿戴设备能够对个体进行具有良好通用性的连续血压监测,并在个人医疗保健应用中显示出有前景的潜力。