Noncontact Sleep Apnea-hypopnea Events Detection Using a K-band Biomedical Radar

被引:0
|
作者
Dong, Shuqin [1 ,2 ]
Wen, Li [1 ,2 ]
Ye, Yangtao [1 ,2 ]
Zhang, Jing [3 ]
Gu, Changzhan [1 ,2 ]
Mao, Junfa [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, State Key Lab Radio Frequency Heterogeneous Integ, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, MoE Key Lab Artificial Intelligence, Shanghai 200240, Peoples R China
[3] Shanghai Jiao Tong Univ, Shanghai Childrens Med Ctr, Dept Resp, Sch Med, Shanghai, Peoples R China
基金
美国国家科学基金会;
关键词
Airflow; Biomedical radar; Respiratory disorder; Sleep apnea; Noncontact detection;
D O I
10.1109/IWS61525.2024.10713614
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The golden standard of nocturnal respiratory function assessment is polysomnography (PSG) especially for diagnosis of sleep apnea-hypopnea syndrome (SAHS). However, the use of PSG sensors usually obstructs the patients' breathing, causing discomfort. One of the most important signals in PSG to assess respiratory function is airflow, especially for sleep apnea detection. Radar-based contactless detection technique provides a non-contact monitor way to overcome such limitation. Aiming at automatic sleep respiratory events detection, a 24-GHz biomedical radar sensor combined with apnea detection algorithm is developed to provide accurate continuous measurement of respiratory waveform during sleep. Through the overnight experiment, the radar data and PSG data were simultaneously recorded. Professional sleep technicians' manual assessments of sleep respiratory events based on PSG data are found to be consistent with results automatically determined using radar data, which makes the at-home monitoring possible in the future.
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页数:3
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