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Given the significant impact of sleep on overall health, radar technology offers a promising, non‐invasive, and cost‐effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)‐based classification. In this study, we employed an attention‐based bidirectional long short‐term memory (Attention Bi‐LSTM) model to accurately predict sleep stages using 60...
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