Key result
The windowed on-line generalised likelihood ratio (GLR) test algorithm effectively detected abrupt changes in real ECG signals in real-time situations.
The proposed generalised likelihood ratio algorithm, particularly the windowed on-line version, effectively detects abrupt changes in real-time ECG signals.
This study is devoted to detection of abrupt changes in electrocardiogram (ECG). A linear time-variant model with Gaussian white noise is used to describe the real ECG signal, based on the estimated system parameters and tuned covariances of noise, the off-line and on-line generalised likelihood ratio (GLR) tests for ECG signal are developed for change detection. For comparison, the test algorithm uses Levinson, recursive least squares (RLS) methods to obtain the filter models parameters of ECG. Furthermore, windowed on-line GLR test algorithm is developed, which works more effectively in real-time situation. The simulation results with real data show the effectiveness of the application.
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Xia et al. (2010) studied ECG signal analysis. Generalised likelihood ratio (GLR) algorithm vs. Levinson and recursive least squares (RLS) methods was evaluated on Detection of abrupt changes in ECG. The windowed on-line generalised likelihood ratio (GLR) test algorithm effectively detected abrupt changes in real ECG signals in real-time situations.
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