Identifying and removing low quality seismocardiogram cycles

心血管疾病（CVD）影响着160万加拿大人的生活，是加拿大第二大死亡原因。CVD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)是一家总部位于弗吉尼亚州的公司，开发用于预防和诊断心血管疾病的无创心脏监测的软件和硬件技术。特别是，HFM的专有技术测量心脏振动，这被称为心震图（SCG）。SCG可以通过在胸骨上放置加速度计来捕获，并提供有关心脏机械方面的信息。由于SCG信号对由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来源是加速计传感器在胸骨上的不适当放置。在这些情况下，SCG信号具有低质量（LQ）并且心脏信息的提取是不可靠的。因此，本建议的目的是开发一种算法，（1）可以容纳运动伪影，（2）可以在分析之前自动识别和删除LQ SCG周期。这样的算法必须学习可识别和可接受的SCG心动周期的形态学，并且当不能提取重要特征时丢弃这些周期。这一步在心脏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，以提高其准确性，可靠性和可用性，以评估心脏性能。

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.