A neural network with asymmetric basis functions for feature extraction of ECG P waves

IEEE Transactions on Neural Networks

Volumn 12, Issue 5, 2001, Pages 1252-1255

  Botter, Eduardo De Azevedo ^a   Nascimento Jr , Cairo L ^b   Yoneyama, Takashi ^b  

^a INSTITUTO DANTE PAZZANESE DE CARDIOLOGIA   (Brazil)

^b INSTITUTO TECNOLÓGICO DE AERONÁUTICA   (Brazil)

Author keywords

Asymmetric basis functions; Electrocardiography; Feature extraction; Feedforward neural networks

Indexed keywords

BACKPROPAGATION; ELECTROCARDIOGRAPHY; FEATURE EXTRACTION; FUNCTIONS; KALMAN FILTERING; LEARNING ALGORITHMS; LEARNING SYSTEMS;

ASYMMETRIC BASIS FUNCTIONS; NEURAL NETWORK TRAINING; PATTERN CLUSTERING;

FEEDFORWARD NEURAL NETWORKS;

EID: 0035439831     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.950154     Document Type: Letter

References (16)

1. A comparison of the noise sensitivity of nine QRS detection algorithms
2. Feature extraction and state identification in biomedical signals using hierarchical fuzzy clustering
3. Detection of the P and T waves in an ECG
4. ECG pattern recognition and classification using nonlinear transformations and neural networks: A review
5. MIT-BIH database
6. Artificial neural networks in control and optimization
7. A new method to detect P waves in ECG signals
8. A digital filter for the QRS complex detection
9. Automated recognition of corrupted arterial waveforms using neural network techniques
10. Application of adaptive signal processing for determining the limits of P and T waves in an ECG
11. ECG analysis using nonlinear PCA neural networks for ischemia detection
12. ANN-based QRS-complex analysis of ECG
13. Approach to recognition of ECG P waves based on approximating functions