希尔伯特-黄变换
心跳
算法
计算机科学
信号(编程语言)
傅里叶变换
心脏超声心动图
模式识别(心理学)
数学
人工智能
滤波器(信号处理)
医学
心脏病学
计算机视觉
数学分析
计算机安全
程序设计语言
作者
Jingda Feng,Weifen Huang,Jian Jin,Yanlei Wang,Xiang Zhang,Qijie Li,Xuejun Jiao
标识
DOI:10.3389/fphys.2023.1201722
摘要
The Ballistocardiogram (BCG) is a vibration signal that is generated by the displacement of the entire body due to the injection of blood during each heartbeat. It has been extensively utilized to monitor heart rate. The morphological features of the BCG signal serve as effective indicators for the identification of atrial fibrillation and heart failure, holding great significance for BCG signal analysis. The IJK-complex identification allows for the estimation of inter-beat intervals (IBI) and enables a more detailed analysis of BCG amplitude and interval waves. This study presents a novel algorithm for identifying the IJK-complex in BCG signals, which is an improvement over most existing algorithms that only perform IBI estimation. The proposed algorithm employs a short-time Fourier transform and summation across frequencies to initially estimate the occurrence of the J wave using peak finding, followed by Ensemble Empirical Mode Decomposition and a regional search to precisely identify the J wave. The algorithm’s ability to detect the morphological features of BCG signals and estimate heart rates was validated through experiments conducted on 10 healthy subjects and 2 patients with coronary heart disease. In comparison to commonly used methods, the presented scheme ensures accurate heart rate estimation and exhibits superior capability in detecting BCG morphological features. This advancement holds significant value for future applications involving BCG signals.
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