Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology

Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology

Wearable accelerometers are widely used as an ecologically valid and scalable solution for long-term at-home sleep monitoring in both clinical research and care. In this study, we applied a deep learning domain adversarial convolutional neural network (DACNN) model to this task and demonstrated that...

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Bibliographic Details
Main Authors: Adonay S. Nunes, Matthew R. Patterson, Dawid Gerstel, Sheraz Khan, Christine C. Guo, Ali Neishabouri
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
sleep
accelerometer
wearable
deep learning
Online Access:https://www.mdpi.com/1424-8220/24/24/7982
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