Detection of the electrocardiogram P-wave using wavelet analysis
- California Univ., Davis, CA (United States). Dept. of Applied Science
- Lawrence Livermore National Lab., CA (United States)
Since wavelet analysis is an effective tool for analyzing transient signals, we studied its feature extraction and representation properties for events in electrocardiogram (EKG) data. Significant features of the EKG include the P-wave, the QRS complex, and the T-wave. For this paper the feature that we chose to focus on was the P-wave. Wavelet analysis was used as a pre-processor for a backpropagation neural network with conjugate gradient learning. The inputs to the neural network were the wavelet transforms of EKGs at a particular scale. The desired output was the location of the P-wave. The results were compared to results obtained without using the wavelet transform as a pre-processor.
- Research Organization:
- Lawrence Livermore National Lab., CA (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 10146126
- Report Number(s):
- UCRL-JC--115855; CONF-940449--7; ON: DE94010791
- Country of Publication:
- United States
- Language:
- English
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