Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Onatrio, Canada.
Nat Biomed Eng. 2023 Oct;7(10):1229-1241. doi: 10.1038/s41551-023-01098-y. Epub 2023 Oct 2.
Cardiovascular health is typically monitored by measuring blood pressure. Here we describe a wireless on-skin system consisting of synchronized sensors for chest electrocardiography and peripheral multispectral photoplethysmography for the continuous monitoring of metrics related to vascular resistance, cardiac output and blood-pressure regulation. We used data from the sensors to train a support-vector-machine model for the classification of haemodynamic states (resulting from exposure to heat or cold, physical exercise, breath holding, performing the Valsalva manoeuvre or from vasopressor administration during post-operative hypotension) that independently affect blood pressure, cardiac output and vascular resistance. The model classified the haemodynamic states on the basis of an unseen subset of sensor data for 10 healthy individuals, 20 patients with hypertension undergoing haemodynamic stimuli and 15 patients recovering from cardiac surgery, with an average precision of 0.878 and an overall area under the receiver operating characteristic curve of 0.958. The multinodal sensor system may provide clinically actionable insights into haemodynamic states for use in the management of cardiovascular disease.
心血管健康通常通过测量血压来监测。在这里，我们描述了一种无线皮肤系统，它由胸部心电图同步传感器和外周多光谱光体积描记法传感器组成，用于连续监测与血管阻力、心输出量和血压调节相关的指标。我们使用传感器数据来训练支持向量机模型，以对血流动力学状态（由于暴露于热或冷、体育锻炼、屏气、施行瓦尔萨尔瓦动作或术后低血压时使用血管加压药）进行分类，这些状态独立影响血压、心输出量和血管阻力。该模型基于 10 名健康个体、20 名高血压患者进行血流动力学刺激和 15 名心脏手术后恢复患者的传感器数据未见子集，对血流动力学状态进行分类，平均精度为 0.878，整体接收器操作特征曲线下面积为 0.958。多节点传感器系统可为心血管疾病管理中血流动力学状态提供临床可操作的见解。
