{"title":"ECG data compression for a portable ECG recorder and transmitter","authors":"Diptee C. Pandhe, H. T. Patil","doi":"10.1109/EIC.2015.7230715","DOIUrl":null,"url":null,"abstract":"The ECG digital signal processing evolved in last decade and the need to store and transmit ECG signal data is continuously increasing. This paper involves analysis of an enhanced ECG compression and de-compression method. The method is evaluated on the basis of different compression and quality parameters like compression ratio (CR), percent root mean square difference (PRD), Signal to noise ratio (SNR), quality score (QS), etc. The compression algorithm includes three sequential processing phases: 1. Pre-processing and classification, 2. Linear transformation, 3. Entropy coding. The compression method is implemented by deciding a particular signal processing / coding algorithm for each of these phases. The de-compression technique is the inverse process of compression and it reconstructs the original signal with negligible loss of information. Finally, the described method is compared with existing ECG compression algorithms.","PeriodicalId":101532,"journal":{"name":"2014 International Conference on Advances in Communication and Computing Technologies (ICACACT 2014)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Advances in Communication and Computing Technologies (ICACACT 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIC.2015.7230715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The ECG digital signal processing evolved in last decade and the need to store and transmit ECG signal data is continuously increasing. This paper involves analysis of an enhanced ECG compression and de-compression method. The method is evaluated on the basis of different compression and quality parameters like compression ratio (CR), percent root mean square difference (PRD), Signal to noise ratio (SNR), quality score (QS), etc. The compression algorithm includes three sequential processing phases: 1. Pre-processing and classification, 2. Linear transformation, 3. Entropy coding. The compression method is implemented by deciding a particular signal processing / coding algorithm for each of these phases. The de-compression technique is the inverse process of compression and it reconstructs the original signal with negligible loss of information. Finally, the described method is compared with existing ECG compression algorithms.
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