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: Nunes, Adonay S., Patterson, Matthew R., Gerstel, Dawid, Khan, Sheraz, Guo, Christine C., Neishabouri, Ali
Other Authors: McGovern Institute for Brain Research at MIT
Format: Article
Published: Multidisciplinary Digital Publishing Institute 2025
Online Access:https://hdl.handle.net/1721.1/157956

Internet

https://hdl.handle.net/1721.1/157956

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