中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
ECG data compression using a neural network model based on multi-objective optimization.

文献类型:期刊论文

作者Zhang, Bo ;  Zhao, Jiasheng ;  Chen, Xiao ;  Wu, Jianhuang
刊名PLOS ONE
出版日期2017
文献子类期刊论文
英文摘要Electrocardiogram (ECG) data analysis is of great significance to the diagnosis of cardiovascular disease. ECG compression should be processed in real time, and the data should be based on lossless compression and have high predictability. In terms of the real time aspect, short-time Fourier transformation is applied to the processing of signal wave for reducing computational time. For the lossless compression requirement, wavelet-transformation that is a coding algorithm can be used to avoid loss of data. In practice, compression is required to avoid storing redundant recording data that are not useful in the diagnosis platform. The obtained data can be preprocessed to remove noise by using wavelet transform, and then a multi-objective optimize neural network model is used to extract feature information. Compared with the existing traditional methods such as direct data processing method and transform method, our proposed compression model has self-learning ability to achieve high data compression ratio at 1: 19 without losing important ECG information and compromising quality. Upon testing, we demonstrated that the proposed ECG data compression method based onmulti-objective optimization neural network is effective and efficient in clinical practice.
URL标识查看原文
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/11967]  
专题深圳先进技术研究院_医工所
作者单位PLOS ONE
推荐引用方式
GB/T 7714
Zhang, Bo , Zhao, Jiasheng , Chen, Xiao ,et al. ECG data compression using a neural network model based on multi-objective optimization.[J]. PLOS ONE,2017.
APA Zhang, Bo , Zhao, Jiasheng , Chen, Xiao ,& Wu, Jianhuang.(2017).ECG data compression using a neural network model based on multi-objective optimization..PLOS ONE.
MLA Zhang, Bo ,et al."ECG data compression using a neural network model based on multi-objective optimization.".PLOS ONE (2017).

入库方式: OAI收割

来源:深圳先进技术研究院

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