Identifying and removing low quality seismocardiogram cycles

识别并消除低质量的心震图周期

• 批准号: 513399-2017
• 负责人: Hodgson, Antony
• 金额: $ 1.82万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640362
• 关键词: Identifying; removing; low; quality; seismocardiogram

Cardiovascular diseases (CVDs) affect the lives of 1.6 million Canadians, and are the second leading cause ofdeath in Canada. CVDs cost the Canadian economy more than $20 Billion annually. Heart Force Medical Inc.(HFM) is a Vancouver-based company developing software and hardware technologies for the noninvasivecardiac monitoring to prevent and diagnose CVDs. In particular, HFM's proprietary technology measures heartvibration, which is referred as the seismocardiogram (SCG). SCGs can be captured by placing an accelerometeron the sternum, and provide information about mechanical aspects of the heart. Due to the inherent sensitivityof the SCG signal to motion artifacts caused by respiration or body movements, sophisticated algorithms haveto be developed to remove or minimize the effect of these artifacts. Another source of inadequate reliability ofthe SCG signal is the inappropriate placement of the accelerometer sensor on the sternum. In these situations,the SCG signals are of low quality (LQ) and the extraction of cardiac information is unreliable. Therefore, thepurpose of this proposal is to develop an algorithm that (1) can accommodate motion artifacts, and (2) canautomatically identify and remove LQ SCG cycles prior to analysis. Such an algorithm has to learn themorphology of recognizable and acceptable SCG cardiac cycles and discard those cycles when important datacannot be extracted. This step is crucial in the overall electromechanical assessment of cardiac function. Thedeveloped algorithm will be deployed in relevant HFM devices to increase their accuracy, reliability, andusability to evaluate cardiac performance.

心血管疾病影响着160万加拿大人的生活，是加拿大第二大死因。心血管疾病每年给加拿大经济造成的损失超过200亿美元。心脏力量医疗公司(HFM)是一家总部位于温哥华的公司，开发用于非侵入性心脏监测的软件和硬件技术，以预防和诊断心血管疾病。特别是，HFM的专利技术测量心脏振动，被称为地震心动图(SCG)。可以通过在胸骨上放置加速计来捕捉SCG，并提供关于心脏机械方面的信息。由于SCG信号对呼吸或身体运动引起的运动伪影的固有敏感性，必须开发复杂的算法来消除或最小化这些伪影的影响。SCG信号可靠性不足的另一个原因是加速度计传感器在胸骨上放置不当。在这些情况下，SCG信号的质量(LQ)低，心脏信息的提取不可靠。因此，该方案的目的是开发一种算法，该算法(1)可以适应运动伪影，(2)可以在分析之前自动识别和去除LQ SCG循环。这样的算法必须学习可识别和可接受的SCG心动周期的形态，并在无法提取重要数据时丢弃这些周期。这一步在心功能的整体机电评估中至关重要。开发的算法将部署在相关的HFM设备中，以提高其评估心脏性能的准确性、可靠性和易用性。