Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles
Objective Obstructive sleep apnea is a global health concern, and several tools have been developed to screen its severity. However, most tools focus on respiratory events instead of sleep arousal, which can also affect sleep efficiency. This study employed easy-to-measure parameters—namely heart ra...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2023-10-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076231205744 |