No abstract

Early detection of arrhythmia and effective treatment can prevent deaths caused by cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the electrocardiogram (ECG) beat-by-beat, but this is usually time-consuming and laborious. In the paper, we propose an automatic ECG classification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Network (CNN). CWT is used to decompose ECG signals to obtain different time-frequency components, and CNN is used to extract features from the 2D-scalogram composed of the above time-frequency components. Considering the surrounding R peak interval (also called RR interval) is also useful for the diagnosis of arrhythmia, four RR interval features are extracted and combined with the CNN features to input into a fully connected layer for ECG classification. By testing in the MIT-BIH arrhythmia database, our method achieves an overall performance of 70.75%, 67.47%, 68.76%, and 98.74% for positive predictive value, sensitivity, F1-score, and accuracy, respectively. Compared with existing methods, the overall F1-score of our method is increased by 4.75~16.85%. Because our method is simple and highly accurate, it can potentially be used as a clinical auxiliary diagnostic tool.

In this work, chitosan (CS) decorated metronidazole (MTZ) microcapsules (CS@MTZ) were synthesized and used as a cross-linker for the preparation of a poly(vinyl alcohol) (PVA) injectable hydrogel by dynamic covalent bonding and ionic interaction through a 4-carboxyphenylboronic acid bridge. The use of MTZ microcapsules efficiently slowed down the release rate of the hydrophilic antibiotic from the hydrogel matrix. Besides, the hydrophobicity of the microcapsules endows the PVA@CS@MTZ hydrogel to be sticky to a substrate in wet conditions, under a suggested mechanism of evicting the water boundary layer on the substrate. The sustained release behavior endowed a prolonged bacteriostasis ability of the hydrogel formulation for up to 14 days in vitro, and the bioadhesive property as well as the injectability of the hydrogel benefited the topical delivery of MTZ in periodontal pockets and exhibited desirable antibacterial capacity in 1 week on the rat periodontitis model.

Aortic pulse wave velocity, calculated from pulse transit time (PTT), is often used as an indicator of arterial stiffness and suggested to be standardized for heart rate (HR). This study aimed to determine whether PTT obtained directly from radial arterial waveforms could be used to assess arterial stiffness and the effect of HR on it. Measurements of anthropometric parameters, blood pressure (BP) and radial PTT were taken in 266 apparently healthy adults (113 men and 153 women; age 18-78 years). BP and radial PTT were measured in a subgroup of 11 young subjects (seven men and four women, age 24-35 years) in a 3-month follow-up study, which aimed to investigate the effect of HR changes. Radial PTT was significantly higher in men compared with women (0.116±0.022 s compared with 0.103±0.031 s, Po0.001). It was inversely related to age in men and women (r¼À0.838 and r¼À0.804, respectively, Po0.01 for both). Multiple regression analysis showed that HR was a potent predictor of radial PTT in addition to age, sex and systolic BP. There was no significant change in radial PTT when HR ranged from 60 to 75 b.p.m. A significant decrease was found in radial PTT when HR was up to 80 b.p.m. (Po0.01). These findings indicate that the simple and easily obtainable radial PTT could be a useful index of arterial stiffness, and HR changes should be considered when it is up to 80 b.p.m.