ECG data compression by corner detection

An ECG sampled at a rate of 360, 500 samples s^-1 or more produces a large amount of redundant data that are difficult to store and transmit. A process is therefore required to represent the signals with clinically acceptable fidelity and with the least code bits possible. In the paper, a real-time ECG data compressing algorithm, CORNER, is presented. CORNER is an efficient algorithm which locates significant samples and at the same time encodes the linear segments between them using linear interpolation. The samples selected include, but are not limited to, the samples that are significantly displaced from the encoded signal such that the allowed maximum error is limited to a constant e{open} which is specified by the users. The way in which CORNER computes the displacement of a sample from the encoded signal guarantees that the high activity regions are more accurately coded. The results are compared with those of the well known data compression algorithm, AZTEC, which is also a real-time algorithm. It is found that, under the same bit rate, a considerable improvement of the signal-to-noise ratio (SNR) and root mean square error (RMS_err) can be achieved by employing the proposed CORNER algorithm. An average value of SNR (RMS_err) of 27·0 dB (5·668) can be achieved even at an average bit rate of 0·79 bit sample^-1 by employing CORNER, whereas the average value of SNR (RMS_err) achieved by AZTEC under the same bit rate is 16·60 dB (19·368).