IEEE J Biomed Health Inform. 2019 Jan;23(1):334-341. doi: 10.1109/JBHI.2018.2808413. Epub 2018 Feb 21.
This paper addresses the detection of emboli from signals acquired with a new miniaturized and portable transcranial Doppler ultrasound device. The use of this device enables outpatient monitoring but increases the number of artifacts. These artifacts usually come from the patient voice and motion and can be superimposed to emboli. For this reason and because of the scarcity of emboli compared to artifacts, reliably detect emboli is a challenging task. As an example, the 11809 s of signal used in this study contained 0.06 % of embolic events and 10.14 % of artifacts. Herein, we propose an automatic and sequential approach. The method is based on sequential determination of high intensity transient signals. We also define efficient features to describe emboli in the time frequency representation. On our database, the number of artifacts detected as emboli is divided by more than 10 compared to the other algorithms reported in the literature.
本文探讨了使用新型微型便携式经颅多普勒超声设备获取信号中栓子的检测。该设备的使用可以实现门诊监测,但会增加伪影的数量。这些伪影通常来自患者的声音和运动,并可能与栓子叠加。因此,由于与伪影相比栓子的数量较少,可靠地检测栓子是一项具有挑战性的任务。例如,本研究中使用的 11809 秒信号中,仅包含 0.06%的栓子事件和 10.14%的伪影。在此,我们提出了一种自动的、顺序的方法。该方法基于高强度瞬态信号的顺序确定。我们还定义了有效的特征来描述时频表示中的栓子。在我们的数据库中,与文献中报道的其他算法相比,被错误检测为栓子的伪影数量减少了 10 倍以上。