Automatic sleep scoring with LSTM networks: impact of time granularity and input signals

AM Tăuțan, AC Rossi, B Ionescu - Biomedical Engineering …, 2022 - degruyter.com
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …
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Automatic sleep scoring with LSTM networks: impact of time granularity and input signals.

AM Tăuțan, AC Rossi, B Ionescu - Biomedizinische Technik …, 2022 - europepmc.org
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …

Automatic sleep scoring with LSTM networks: impact of time granularity and input signals

AM Tăuțan, AC Rossi, B Ionescu - Biomedical Engineering …, 2022 - degruyter.com
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …

Automatic sleep scoring with LSTM networks: impact of time granularity and input signals

AM Tăuțan, AC Rossi… - Biomedizinische …, 2022 - pubmed.ncbi.nlm.nih.gov
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …

Automatic sleep scoring with LSTM networks: impact of time granularity and input signals.

AM Tăuțan, AC Rossi… - Biomedical Engineering …, 2022 - search.ebscohost.com
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …