Self-Supervised Learning From Multi-Sensor Data for Sleep Recognition

Self-Supervised Learning From Multi-Sensor Data for Sleep Recognition

Sleep recognition refers to detection or identification of sleep posture, state or stage, which can provide critical information for the diagnosis of sleep diseases. Most of sleep recognition methods are limited to single-task recognition, which only involves single-modal sleep data, and there is no...

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Bibliographic Details
Main Authors: Aite Zhao, Junyu Dong, Huiyu Zhou
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Sleep recognition
sleep diseases
multi-sensor
self-supervised learning
bidirectional LSTM
CRF
Online Access:https://ieeexplore.ieee.org/document/9093831/

Internet

https://ieeexplore.ieee.org/document/9093831/

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