STAKE Lab, Department of Biosciences and Territory, University of Molise, Pesche (IS), Italy.
ASREM, Molise Region, Campobasso (CB), Italy.
Stud Health Technol Inform. 2022 Jun 6;290:650-654. doi: 10.3233/SHTI220158.
Congestive heart failure (CHF) is a chronic heart disease that causes debilitating symptoms and leads to higher mortality and morbidity. In this paper, we present HARPER, a novel automatic detector of CHF episodes able to distinguish between Normal Sinus Rhythm (NSR), CHF, and no-CHF. The main advantages of HARPER are its reliability and its capability of providing an early diagnosis. Indeed, the method is based on evaluating real-time features and observing a brief segment of ECG signal. HARPER is an independent tool meaning that it does not need any ECG annotation or segmentation algorithms to provide detection. The approach was submitted to complete experimentation by involving both the intra- and inter-patient validation schemes. The results are comparable to the state-of-art methods, highlighting the suitability of HARPER to be used in modern IoMT systems as a multi-class, fast, and highly accurate detector of CHF. We also provide guidelines for configuring a temporal window to be used in the automatic detection of CHF episodes.
充血性心力衰竭（CHF）是一种慢性心脏病，会导致衰弱症状，并导致更高的死亡率和发病率。在本文中，我们提出了 HARPER，这是一种新颖的 CHF 发作自动检测器，能够区分正常窦性节律（NSR）、CHF 和非-CHF。HARPER 的主要优势在于其可靠性和提供早期诊断的能力。事实上，该方法基于评估实时特征和观察 ECG 信号的简短片段。HARPER 是一种独立的工具，这意味着它不需要任何 ECG 注释或分割算法来提供检测。该方法通过涉及内部和患者间验证方案进行了完整的实验。结果可与最先进的方法相媲美，突出了 HARPER 适合用作现代 IoMT 系统中的多类、快速和高精度 CHF 检测器。我们还提供了用于自动检测 CHF 发作的时间窗口配置指南。
