Multi Sensor Fusion for Remote Circulatory Monitoring

用于远程循环监测的多传感器融合

• 批准号: 6725971
• 负责人: Haruhiko Harry Asada
• 金额: $ 22.26万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2005-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6725971
• 关键词: biomedical equipment development; biosensor device; blood circulation; blood flow measurement; blood pressure; cardiac output; clinical research; computer program /software; hemodynamics; human subject; noninvasive diagnosis; patient monitoring device

DESCRIPTION (provided by applicant): Remote assessment of circulation is expected to be valuable in protecting individuals in the community predisposed to circulatory dysfunction, individuals involved in hazardous duties, and traditional hospital patients. This task requires sensors on the body, which ideally will be worn for days at a time during a diversity of activities, yielding real time data. Several modalities, such as photoplethysmography and electrical bioimpedance, satisfy the criteria for truly wearable biosensors; they are unobtrusive, non-invasive, and power efficient. However, the data currently derived from these sensors are not adequate for circulatory monitoring during activities of daily living, or more demanding activities such as fitness training or military battle. There are four key shortcomings in practice today: each measured signal is (a) altered by the location in which the measurement is made; (b) determined by an uncertain combination of central hemodynamic and local effects; (c) lacking in complete information necessary to characterize the central state; and (d) corrupted by local sources of noise such as physical movement and muscular bioelectrical signals. To overcome these problems, we propose a new approach to multiple sensor fusion: the multichannel blind system identification (MBSI) technique. MBSI allows the estimation of both an unknown input and the unknown dynamics from a set of related outputs. The technique is now used in wireless communication systems in which a single broadcast signal is altered by transmission across different paths then received simultaneously by multiple receivers. Similarly, it is proposed that the signals from multiple circulatory biosensors may be processed with MBSI algorithms. The MBSI algorithms may provide a systematic way of fusing multiple non-invasive biosensors in real-time to determine the cardiac output and other global hemodynamic parameters, as well as to characterize the vascular dynamics that are unique to each sensor channel. Milestones for this project will include the design of wearable, unobtrusive, low-power, non-invasive sensor hardware and MBSI data-fusion algorithms capable of 1) long-term cardiac output estimation, 2) continuous arterial blood pressure monitoring, and 3) detection of focal peripheral vascular pathologies.

描述（由申请人提供）：预计流通的远程评估对于保护社区中的个体易于循环功能障碍，涉及危险职责的人和传统医院患者有价值。这项任务需要身体上的传感器，理想情况下将在各种活动中一次佩戴几天，从而产生实时数据。几种方式，例如光杀解物学和电势力，满足了真正可穿戴生物传感器的标准。它们没有引人注目的，无创的和有效的效率。但是，目前从这些传感器中得出的数据不足以进行日常生活活动期间的循环监测，或者更苛刻的活动，例如健身训练或军事战斗。如今，实践中有四个关键的缺点：每个测量的信号都会因进行测量的位置而改变； （b）通过中枢血流动力学和局部作用的不确定组合确定； （c）缺乏表征中心状态所需的完整信息； （d）被当地噪音的来源损坏，例如身体运动和肌肉发达的生物电信号。为了克服这些问题，我们提出了一种新的传感器融合方法：多通道盲系统识别（MBSI）技术。 MBSI允许估计一组相关输出的未知输入和未知动力学。现在，该技术用于无线通信系统中，其中单个广播信号通过跨不同路径的传输改变，然后由多个接收器同时接收。同样，提议通过MBSI算法处理多个循环生物传感器的信号。 MBSI算法可能会提供一种系统的方式，可以实时融合多个非侵入性生物传感器，以确定心脏输出和其他全局血液动力学参数，并表征每个传感器通道独有的血管动力学。该项目的里程碑将包括设计可穿戴，不引人注目的，低功率，非侵入性传感器硬件和MBSI数据融合算法1）长期心脏输出估算，2）连续动脉血压监测，以及3）检测局灶性外周血管病理学。