1.Inter-patient arrhythmia ECG signal classification based on SVM+XGBoost ensemble classifier
Chenhua XU ; Sichao YE ; Yunjie FENG ; Qingli QIAO
International Journal of Biomedical Engineering 2020;43(5):366-371,375
Objective:To study a classifier used to classify arrhythmia electrocardiogram (ECG) signals under the inter-patient paradigm to improve the accuracy of automatic classification and solve the limitations of manual diagnosis of arrhythmia.Methods:A SVM+XGBoost ensemble classifier with four modules including preprocessing, feature extraction, support vector machine (SVM) training and ensemble classification was constructed. ECG signal was preprocessed, and R-R interval, high-order statistics, local binary patterns and wavelet components were used as features to train independent SVM classifiers. Then, XGboost algorithm was used to integrate independent SVM classifiers and output arrhythmia classification results. The integrated classifiers were trained and tested on MIT-BIH database.Results:The overall classification accuracy of the ensemble classifier for arrhythmia was 0.867 and the average sensitivity was 0.782.Conclusions:The proposed ensemble classifier can realize automatic and accurate classification of arrhythmia ECG signals under the inter-patient paradigm, and can be used for clinical auxiliary diagnosis.
2.Distribution and exposure assessment of phthalic acid esters (PAEs) in indoor dust of Shanghai
Qifan YANG ; Bing SHEN ; Jingting CAI ; Zhongling LIU ; Yi LI ; Sichao FENG ; Yihui ZHOU ; Silan LU ; Hong ZHAO ; Zhiling YE ; Jianjing XIONG
Shanghai Journal of Preventive Medicine 2022;34(3):247-251
Objective To characterize the distribution and assess the exposure to phthalic acid esters (PAEs) in the indoor dust of Shanghai City. Methods Samples were collected from 33 sampling sites, including homes, hotels, offices and public places, in Shanghai in 2018, 2019, and 2020. The samples were pretreated by 100 sieves, extracted and concentrated, and then analyzed by gas chromatography-mass spectrometry in selected ion mode (SIM). Results Results on the characteristics of PAEs in indoor dust in different places showed that concentrations of PAEs were in a range of <0.01-2 464 mg·kg-1.The average concentration of 16 PAEs was 613 mg·kg-1. Bis(2-ethylhexyl) phthalate (DEHP), di-iso-butyl phthalate (DiBP), di-n-butyl phthalate (DBP) and di-n-octyl phthalate (DnOP) were the main components of PAEs in indoor dust, accounting for approximately 99.5% of 16 PAEs. The intake of DEHP, DBP, DEP and BBP was lower than the tolerable daily intake (TDI) and reference doses (RfD) set by EU CSTEE and U.S. EPA. Conclusion Average daily dose (ADD) via indoor dust is estimated, and the order of intake through different pathways is hand-oral intake>skin contact>respiratory inhalation. Exposure risk of PAEs in children is greater than that in adults.