Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4424-4427. doi: 10.1109/EMBC46164.2021.9629981.
Dicrotic Notch (DN) is a distinctive and clinically significant feature of the arterial blood pressure curve. Its automatic identification has been the focus of many kinds of research using either model-based or rule-based methodologies. However, since DN morphology is quite variant following the patient-specific underlying physiological and pathological conditions, its automatic identification with these methods is challenging. This work proposes a hybrid approach that employs both model-based and rule-based approaches to enhance DN detection's generalizability. We have tested our approach on ABP data gathered from 14 pigs. Our result strongly indicates 36% overall mean error improvement with maximum 52% and -11% accuracy enhancement and degradation in extreme cases.
双峰切迹(DN)是动脉血压曲线的一个独特且具有临床意义的特征。使用基于模型或基于规则的方法对其进行自动识别一直是许多研究的重点。然而,由于 DN 形态在很大程度上取决于患者特定的生理和病理状况,因此这些方法在自动识别方面具有一定的挑战性。本工作提出了一种混合方法,该方法同时采用基于模型和基于规则的方法,以提高 DN 检测的泛化能力。我们已经在从 14 头猪收集的 ABP 数据上测试了我们的方法。我们的结果强烈表明,总体平均误差提高了 36%,在极端情况下,准确性最高提高了 52%,最低降低了 11%。