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Algorithmic detection of sleep-disordered breathing using respiratory signals: a systematic review.

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第一作者： Liqing,Yang

第一单位： Key Laboratory of Biorheological Science and Technology of Ministry of Education, Chongqing University, Chongqing, People's Republic of China.;Chongqing Medical Electronics Engineering Technology Research Center, Chongqing University, Chongqing, People's Republic of China.

作者： Liqing,Yang ^[1] ; Zhimei,Ding ^[1] ; Jiangjie,Zhou ^[2] ; Siyuan,Zhang ^[1] ; Qi,Wang ^[2] ; Kaige,Zheng ^[2] ; Xing,Wang ^[3] ; Lin,Chen ^[3]

作者单位： Key Laboratory of Biorheological Science and Technology of Ministry of Education, Chongqing University, Chongqing, People's Republic of China.;Chongqing Medical Electronics Engineering Technology Research Center, Chongqing University, Chongqing, People's Republic of China. ^[1] Chongqing Medical Electronics Engineering Technology Research Center, Chongqing University, Chongqing, People's Republic of China.;Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology, Chongqing, People's Republic of China. ^[2] Key Laboratory of Biorheological Science and Technology of Ministry of Education, Chongqing University, Chongqing, People's Republic of China.;Chongqing Key Laboratory of Artificial Intelligence and Service Robot Control Technology, Chongqing, People's Republic of China. ^[3]

关键词 deep learning machine learning respiratory signal sleep-disordered breathing threshold rule-based algorithms

医学主题词人类(Humans);算法(Algorithms);呼吸(Respiration);信号处理, 计算机辅助(Signal Processing, Computer-Assisted);睡眠呼吸暂停综合征(Sleep Apnea Syndromes)

DOI 10.1088/1361-6579/ad2c13

PMID 38387048

发布时间 2026-05-22

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