ECG signal compression based on B-spline approximation

Abstract

In general, electrocardiogram(ECG) signals are sampled with a frequency over 200Hz and stored for a long time. It is required to compress data efficiently for storing and transmitting them. In this paper, a method for compression of ECG data is proposed, using by Non Uniform B-spline approximation, which has been widely used to approximation theory of applied mathematics and geometric modeling. ECG signals are compressed and reconstructed using B-spline basis function which curve has local controllability and control a shape and curve in part. The proposed method selected additional knot with each step for minimizing reconstruction error and reduced time complexity. It is established that the proposed method using B-spline approximation has good compression ratio and reconstruct besides preserving all feature point of ECG signals, through the experimental results from MIT-BIH Arrhythmia database.

ECG Signal Compression based on Adaptive Multi-level Code

“…직접 압축 방식은 심전도 신호 데이터의 값을 시 간 영역에서 해석하여 압축을 한다. 이 방법에는 Turning-Point, AZTEC, CORTES, FAN, DCPM, 곡률기 반 압축, B-spline 기반 압축 등이 있다 [6][7][8][9][10][11] …”