Compression And Streaming Of Large-Scale ECG Data For Teledata Sharing

Telemedicine is an effective way to sharing healthy care resources. Remotediagnosis and consultation are important parts of it. ECG especially the large-scaleECG data such as dynamic ECG offers plenty information for the diagnosis ofcardiovascular diseases. So the teledata sharing of large-scale ECG is the principalissue on remote diagnosis and consultation of cardiovascular diseases.This dissertation was brought forward for the solution of teledata sharing oflarge-scale ECG data. The main works are large-scale ECG data compression andstreaming which are the key issues on teledata sharing. Detailed works arefollowings:Firstly, expounded the basic fundamental and characteristics of lossless ECGdata compression and streaming; reviewed the development of these techniques inboth domestic and foreign related field; and indicated the main problems.Secondly, proposed a lossless ECG data compression algorithm which is basedon JPEG2000 and integrated both 1D and 2D compression method. The proposedalgorithm has high compression rate and excellent performance.Thirdly, designed a solution for teledata sharing of large-scale ECG whichranged ECG data by segments, sample rates and leads, applied the proposedcompression algorithm; defined the organizing frame of large-scale ECG data.Finally, evaluated the proposed lossless ECG compression algorithm using theall forty-eight records in MIT-BIH Arrhythmia database; synthetically andquantificationally evaluated the performance of the proposed solution for teledatasharing of large-scale ECGCompared with other algorithms by the same test data, the proposed ECGlossless compression algorithm shows better compression result; the proposedsolution for teledata sharing of large-scale ECG could be applied on remote diagnosisand consultation of cardiovascular diseases with well performance.