DeepArrNet: An Efficient Deep CNN Architecture for Automatic Arrhythmia Detection and Classification From Denoised ECG Beats.
Tanvir MahmudShaikh Anowarul FattahMohammad SaquibPublished in: IEEE Access (2020)
Keyphrases
- beat classification
- mit bih arrhythmia database
- ecg signals
- heart rate variability
- classification accuracy
- features extraction
- automatic classification
- pattern recognition
- feature selection
- robust detection
- automatic detection
- feature vectors
- support vector machine
- decision trees
- statistical classification
- feature extraction
- text classification
- detection algorithm
- detection method
- semi automatic
- classification method
- software architecture
- convolutional neural network
- classification scheme
- support vector
- image classification
- object detection
- management system
- detection rate
- noise reduction
- training set
- classification algorithm
- multiscale
- higher order statistics
- denoising
- feature space
- image processing
- machine learning