An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Data
2.2. Model Architecture
2.3. Theoretical Gains of 1-D OctConv
2.4. Visualization of Class Discriminative Regions
3. Results and Discussion
3.1. Experiment Setup
3.2. Evaluation Metrics
3.3. Results and Interpretations
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Ratio (α) | 0 | 0.25 | 0.5 | 0.75 |
---|---|---|---|---|
#FLOPs Cost | 100% | 78% | 63% | 53% |
Memory Cost | 100% | 88% | 75% | 63% |
α | F1-Test | F1-Cross | CNN-GFLOPs | GRU-FC-GFLOPs | Inference Time (s) |
---|---|---|---|---|---|
0 | 0.907 | 0.872 ± 0.048 | 0.52 | 3 × 10−4 | 0.59 |
0.25 | 0.911 | 0.874 ± 0.054 | 0.42 | 3 × 10−4 | 0.55 |
0.5 | 0.901 | 0.869 ± 0.059 | 0.34 | 3 × 10−4 | 0.48 |
0.75 | 0.894 | 0.866 ± 0.058 | 0.29 | 3 × 10−4 | 0.45 |
Types of Noise | SNR Level (dB) | Motion Noise | ||
---|---|---|---|---|
50.6 | 36.8 | 29.12 | ||
F1 | 0.815 | 0.739 | 0.627 | 0.844 |
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Vo, K.; Le, T.; Rahmani, A.M.; Dutt, N.; Cao, H. An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram. Sensors 2020, 20, 3757. https://doi.org/10.3390/s20133757
Vo K, Le T, Rahmani AM, Dutt N, Cao H. An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram. Sensors. 2020; 20(13):3757. https://doi.org/10.3390/s20133757
Chicago/Turabian StyleVo, Khuong, Tai Le, Amir M. Rahmani, Nikil Dutt, and Hung Cao. 2020. "An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram" Sensors 20, no. 13: 3757. https://doi.org/10.3390/s20133757
APA StyleVo, K., Le, T., Rahmani, A. M., Dutt, N., & Cao, H. (2020). An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram. Sensors, 20(13), 3757. https://doi.org/10.3390/s20133757