多信息交互的睡眠呼吸暂停综合症无扰检测系统
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摘要
针对目前睡眠呼吸暂停综合症(SAS)的治疗只能借助多导睡眠监测仪(PSG)监测和专业医师的诊断的现状,开展智能、便捷、无干扰监测睡眠呼吸暂停综合症系统的研究。该系统综合麦克风阵列、光纤和柔性压力阵列多种传感器采集人体多种生理信息,为SAS提供一种无扰动检测方法。基于人体鼾声强度、心率、呼吸率、睡姿等生理信息,建立多信息交互的系统模型,评判人体的睡眠风险指数,对SAS进行量化分级,并生成基于大数据分析的个性化报告。系统提供丰富可视化界面,显示人体生理信息及分析结果;不干扰人体自然睡眠,可以在家庭环境中长期跟踪记录个人鼾症变化;使用简单、便捷,促进了智慧医疗的家庭应用。
At present,the treatment of sleep apnea syndrome(SAS) can only rely on the monitoring of polysomnography(PSG) and the diagnosis of professional doctors.In view of this condition,the research on intelligent,convenient and non-interference monitoring of sleep apnea syndrome is carried out.This system integrates microphone array,optical fiber and flexible pressure array sensors to collect multiple kinds of physiological information of human body,and provides a non-disturbance detection method for SAS.Based on physiological information such as snoring intensity,heart rate,breathing rate and sleeping posture,a systematic model of multi-information interaction is established to evaluate human sleep risk index,quantify and classify apnea syndrome,and generate personalized reports based on big data analysis.The system provides a rich visual interface to display human physiological information and analysis results; does not interfere with human natural sleep; it can long term track and record individual snoring changes in home environment.It is simple and convenient to use,and promotes the home application of intelligent medical.
At present,the treatment of sleep apnea syndrome(SAS) can only rely on the monitoring of polysomnography(PSG) and the diagnosis of professional doctors.In view of this condition,the research on intelligent,convenient and non-interference monitoring of sleep apnea syndrome is carried out.This system integrates microphone array,optical fiber and flexible pressure array sensors to collect multiple kinds of physiological information of human body,and provides a non-disturbance detection method for SAS.Based on physiological information such as snoring intensity,heart rate,breathing rate and sleeping posture,a systematic model of multi-information interaction is established to evaluate human sleep risk index,quantify and classify apnea syndrome,and generate personalized reports based on big data analysis.The system provides a rich visual interface to display human physiological information and analysis results; does not interfere with human natural sleep; it can long term track and record individual snoring changes in home environment.It is simple and convenient to use,and promotes the home application of intelligent medical.
引文
[1] 殷善开,易红良,曹振宇.阻塞性睡眠呼吸暂停低通气综合症[M].北京:科学技术文献出版社,2006.
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[8] 杨枢,王璠.多模光纤传感器力学特性分析及其应用[D].广州:暨南大学,2016.
[9] 胡俊浩.生命体征光纤传感器系统及方法:107072565 A[P].2017- 08- 18.
[10]龚冬梅,孙小芳.基于OTDR的分布式光纤微弯传感系统设计[J].试验技术与管理,2018,35(10):80- 83.
[11]蒋荫球,姜太平,张蕾.基于水平集方法和神经网络的人体睡姿识别[J].工业控制计算机,2013,26(5):88- 90.
[12]任志强,李洋,郭世杰,等.基于模糊粗糙集的睡姿压力图像识别[J].计算机工程与应用,2018,54(3):172- 177.
[13]杨先军.柔性力敏传感器及其应用技术研究[D].合肥:中国科学技术大学,2012.
[14]汪飞跃,姚志明,许胜强,等.基于柔性力敏传感器的左右脚动态识别方法[J].传感器技术学报,2015,28(7):965- 971.
[2] 赵蕾,黄席珍.睡眠打蔚研究概况[J].中国全科医学,2002(5):412- 414.
[3] 安宁,杨卉,杨生明.SAS的研究现状[J].医学综述,2000,6(5):96- 97.
[4] 张文迪,孙晓斐.动态心电图初筛SAS研究进展[J].临床心电学杂志,2016,25(6):442- 444.
[5] OSMEN E Z,OSBOME J,HILL P D,et al.Snoring assessment:do home studies and hospital studies give different results [J].Clinical Otolaryngology & Allied Sciences,1998,23(6):524- 527.
[6] SOLA- SOLER J,JANE R,FIZ J A,et al.Spectral envelope analysis in snoring signals from simple snores and patients with obstructive sleep apnea[C]//Proceeding of the 25th Annual Conference of the IEEE Conference,Cancun,Mexico,September,2003:2527- 2530.
[7] CARTER G.Variance bounds for passively locating an acoustic source with asymmetric line array[J].Acoustical Society of America,1977,62(4):922- 926.
[8] 杨枢,王璠.多模光纤传感器力学特性分析及其应用[D].广州:暨南大学,2016.
[9] 胡俊浩.生命体征光纤传感器系统及方法:107072565 A[P].2017- 08- 18.
[10]龚冬梅,孙小芳.基于OTDR的分布式光纤微弯传感系统设计[J].试验技术与管理,2018,35(10):80- 83.
[11]蒋荫球,姜太平,张蕾.基于水平集方法和神经网络的人体睡姿识别[J].工业控制计算机,2013,26(5):88- 90.
[12]任志强,李洋,郭世杰,等.基于模糊粗糙集的睡姿压力图像识别[J].计算机工程与应用,2018,54(3):172- 177.
[13]杨先军.柔性力敏传感器及其应用技术研究[D].合肥:中国科学技术大学,2012.
[14]汪飞跃,姚志明,许胜强,等.基于柔性力敏传感器的左右脚动态识别方法[J].传感器技术学报,2015,28(7):965- 971.