Wearable Multi-modality Cuffless Blood Pressure Monitoring

摘要 连续血压是麻醉、手术等过程中最重要的监测指标之一 重症监护室（ICU）。低血压和高血压都会损害重要器官的功能 (e.g.脑、心脏和肾脏），术中低血压与术后死亡率相关， 因此，尽快检测血压变化以及时进行干预或治疗非常重要。 然而，目前用于BP监测的金标准技术，即侵入性动脉线（a线）， 患者痛苦（身体疼痛）并增加感染风险。在美国，大约有8万人 由动脉导管引起的溪流感染每年都有报告。由于相关的固有风险 对于a-line，它仅用于临床指征的高风险手术或ICU患者。由于a线 风险和不适，尽管每年全世界有超过3亿例手术， 小部分接受连续BP监测。此外，尽管生命体征（ECG、脉搏血氧饱和度、BP等） 监测在手术室和ICU中是常规的，目前大多数监测设备都固定在个体中， 房间，这导致病人监测的差距，病人运输过程中的事故，以及额外的工作， 在离开和进入新设施时断开和重新连接传感器。无缝的“持续护理” 监测-例如从手术室到ICU，包括之间的运输和无需重新连接 传感器-是临床医生的愿望清单的顶部。近年来，已经努力开发便携式 ECG监护仪和“移动的ICU”;然而，到目前为止，还没有连续和无缝的BP监测。 办妥了一批本提案充分利用了相关R21（EB 022271）项目的成果。我们将 开发新的基于机器学习和深度学习的数据融合算法，以使用现有的生命体征， 连续BP监测，然后将其与我们独特的可穿戴患者监测系统集成，形成一个 新型围手术期患者监护系统。我们将根据黄金标准测试系统的性能- line和Finapres BP技术。开发一种功能齐全的技术，用于无创，连续， 无缝BP监测。我们还将开发一个公共数据库，用于未来的BP技术开发。的 提出的多模态算法，无缝BP监测系统和PhysioNet数据库将提供 这是满足无创连续血压监测临床需求的重要步骤。

Abstract Continuous blood pressure (BP) is one of the most critical monitoring parameters during anesthesia, surgery and in intensive care units (ICU). Both hypotension and hypertension can impair the function of vital organs (e.g. brain, heart and kidneys), and intraoperative hypotension is associated with postoperative mortality, which makes it important to detect BP changes as quickly as possible to prompt timely intervention or therapy. However, the current gold standard technology for BP monitoring, an invasive arterial line (a-line), causes patient suffering (physical pain) and increases the risk of infection. In the United States, about 80,000 blood stream infections caused by an arterial catheter are reported annually. Due to the inherent risks associated with a-line, it is used only for clinically indicated high risk surgeries or ICU patients. As a result of the a-line risks and discomforts, even though more than 300 million surgeries are performed worldwide each year, only a small portion receive continuous BP monitoring. In addition, although vital sign (ECG, pulse oximetry, BP etc) monitoring is routine in surgical rooms and ICUs, currently most monitoring devices are fixed in individual rooms, which result in gaps in patient monitoring, accidents during patient transport process, and extra work to disconnect and reconnect sensors when leaving and entering a new facility. Seamless “continuum of care” monitoring—for instance from surgical room to ICUs, including transport in between and without reconnecting sensors—is on top of the wish list by clinician. In recent years, efforts have been made to develop portable ECG monitors and “mobile ICUs”; however so far, no continuous and seamless BP monitoring has been achieved. This proposal fully leverages the outcomes from the related R21 (EB022271) project. We will develop novel machine learning and deep learning based data fusion algorithms to use existing vital signs for continuous BP monitoring, then integrate them with our unique wearable patient monitoring system to form a novel perioperative patient monitoring system. We will test the system’s performance against gold standard a- line and Finapres BP technologies. to develop a fully functional technology for noninvasive, continuous, and seamless BP monitoring. We will also develop a public database for future BP technology development. The proposed multimodality algorithms, seamless BP monitoring system and PhysioNet database will provide major steps forward to meet the clinical need for noninvasive continuous BP monitoring.