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Dynamic ECG monitoring will produce a lot of data, and ECG compression becomes very important with the increasing of sampling frequency and resolution. I present ECG compression and reconstruction algorithm with high compression ratio and low loss. The filter module consists of a low-pass filter, a trap filter and a median filter, which filters out the main noise in the ECG signal. The eighth-order low pass Butterworth filter is used to filter out the EMG interference with a cut-off frequency of 75hz. The sixth-order Band Butterworth filter is used to filter out the power interference with lower limit and upper limit of 49 Hz and 51 Hz respectively. The bipolar median filter is used to correct the drift of breathing.
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Implementation of Machine Learning Algorithms
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