WaveSleepNet: An Interpretable Network for Expert-like Sleep Staging

arXiv:2404.15342v1 Announce Type: cross
Abstract: Although deep learning algorithms have proven their efficiency in automatic sleep staging, the widespread skepticism about their "black-box" nature has limited its clinical acceptance. In this study, we propose WaveSleepNet, an interpretable neural network for sleep staging that reasons in a similar way to sleep experts. In this network, we utilize the latent space representations generated during training to identify characteristic wave prototypes corresponding to different sleep stages. The feature representation of an input signal …

abstract algorithms arxiv box clinical cs.lg deep learning deep learning algorithms eess.sp efficiency expert experts nature network neural network skepticism sleep staging study type