MorpheusNet: Resource efficient sleep stage classifier for embedded on-line systems.
Kavoosi A, Mitchell MP, Kariyawasam R, Fleming JE, Lewis P, Johansen-Berg H, Cagnan H, Denison T.
Kavoosi A, et al.
Conf Proc IEEE Int Conf Syst Man Cybern. 2023 Oct;2023:2315-2320. doi: 10.1109/SMC53992.2023.10394274.
Conf Proc IEEE Int Conf Syst Man Cybern. 2023.
PMID: 38384281
Free PMC article.
To address this gap, we aim to provide a model capable of predicting sleep stages in real-time, without requiring access to external computational sources (e.g., mobile phone, cloud). The algorithm is power efficient to enable use on embedded battery powered systems. ...
To address this gap, we aim to provide a model capable of predicting sleep stages in real-time, without requiring access to external computa …