Papers Automatic Sleep Stage Classification
“Automatic Sleep Stage Classification” 태그가 달린 논문 27편 · 필터 해제
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging
Sleep stage classification constitutes an important element of sleep disorder diagnosis. It relies on the visual inspection of polysomnography records by trained sleep technologists. Automated approaches have been design…
Automatic Sleep Stage ClassificationMultimodal Sleep Stage DetectionSleep Stage DetectionSleep StagingSLEEPER: interpretable Sleep staging via Prototypes from Expert Rules
Sleep staging is a crucial task for diagnosing sleep disorders. It is tedious and complex as it can take a trained expert several hours to annotate just one patient's polysomnogram (PSG) from a single night. Although dee…
Automatic Sleep Stage ClassificationSleep Stage DetectionSleep StagingTowards More Accurate Automatic Sleep Staging via Deep Transfer Learning
Background: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability…
Automatic Sleep Stage ClassificationMultimodal Sleep Stage DetectionSleep Stage DetectionSleep Staging+1Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms
We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50 convolutional layers before subsequent …
Automatic Sleep Stage ClassificationGeneral ClassificationJoint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification
Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This work proposes a joint classification-and-prediction framework based on CNNs for automatic sleep staging, and, subsequently,…
Automatic Sleep Stage ClassificationClassificationGeneral ClassificationSleep Stage Detection+1A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
Automatic sleep staging is a challenging problem and state-of-the-art algorithms have not yet reached satisfactory performance to be used instead of manual scoring by a sleep technician. Much research has been done to fi…
Automatic Sleep Stage ClassificationDimensionality ReductionGeneral ClassificationSleep StagingSleep Stage Classification Based on Multi-level Feature Learning and Recurrent Neural Networks via Wearable Device
This paper proposes a practical approach for automatic sleep stage classification based on a multi-level feature learning framework and Recurrent Neural Network (RNN) classifier using heart rate and wrist actigraphy deri…
Automatic Sleep Stage ClassificationGeneral ClassificationSleep Staging