Automatic model of sleep apnea detection using optimized weighted fusion process of hybrid convolution (1D/2D) efficient attention network from EEG signals
Abstract Background Sleep apnea (SA) is a sleep disorder characterized by breathing interruptions, and it causes significant health risks, including cardiovascular diseases, stroke, and secondary issues such as daytime accidents. The complex nature of SA necessitates accurate and timely diagnosis. T...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-025-01226-7 |
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