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An Automatic Sleep Stage Classification Algorithm Using Improved Model Based Essence Features
The automatic sleep stage classification technique can facilitate the diagnosis of sleep disorders and release the medical expert from labor-consumption work. In this paper, novel improved model based essence features (IMBEFs) were proposed combining locality energy (LE) and dual state space models...
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| Gepubliceerd in: | Sensors (Basel) |
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| Hoofdauteurs: | , , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
MDPI
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7506989/ https://ncbi.nlm.nih.gov/pubmed/32825024 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20174677 |
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