Convolutional Autoencoding and Gaussian Mixture Clustering for Unsupervised Beat-to-Beat Heart Rate Estimation of Electrocardiograms from Wearable Sensors
Heart rate is one of the most important diagnostic bases for cardiovascular disease. This paper introduces a deep autoencoding strategy into feature extraction of electrocardiogram (ECG) signals, and proposes a beat-to-beat heart rate estimation method based on convolution autoencoding and Gaussian...
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| Main Authors: | , , , , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
MDPI AG
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/4afda4a83b3a4b41b7586247173ede0e |
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