Key result
Real-time wavelet transform algorithm detects QRS, P, and T waves to closely reconstruct ECG waveforms.
Why the study?
A real-time technique for detecting characteristic features of ECG waveforms using wavelet transform was developed to improve signal characterization and noise handling.
Population
ECG signals
Comparison
Wavelet transform based algorithm vs external noise corrupted signals
Design
Algorithm development and testing on Texas signal processor chip TMS320C25
Authors
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May enable automated real-time ECG analysis; leaves open clinical validation before practice adoption.
A wavelet transform-based algorithm can be used for real-time detection of ECG features including QRS complex, P, and T waves.
Khobragade et al. (1997) studied ECG waveform analysis. Wavelet transform (WT) based algorithm was evaluated on Detection of QRS complex, P and T waves and reconstruction of ECG signal. A real-time algorithm based on wavelet transforms was developed to detect the QRS complex, P, and T waves of ECG signals and reconstruct a close approximation of the waveform.
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