Automated polysomnogram artifact compensation using the generalized singular value decomposition algorithm.
Automated polysomnogram artifact compensation using the generalized singular value decomposition algorithm.
复制标题
使用广义奇异值分解算法进行自动多导睡眠图伪影补偿。
DOI：
10.1109/iembs.2010.5626213
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Vachtsevanos,George
中科院分区：
文献类型：
--
作者：
Fairley,Jacqueline;Johnson,AshleyN;Georgoulas,George;Vachtsevanos,George
手动/视觉多导睡眠图 (psg) 分析是用于诊断和治疗与睡眠相关的人类病理的标准且常用的程序。当前 PSG 分析的技术趋势侧重于将手动 PSG 分析转化为自动化/计算机化方法。建立高效的自动化人类睡眠分析系统必要的第一步是开发可靠的预处理工具来区分异常值/伪影实例和感兴趣的数据。本文研究了自动化方法的应用，使用广义奇异值分解算法来补偿特定的 psg 伪影。
Manual/visual polysomnogram (psg) analysis is a standard and commonly implemented procedure utilized in the diagnosis and treatment of sleep related human pathologies. Current technological trends in psg analysis focus upon translating manual psg analysis into automated/computerized approaches. A necessary first step in establishing efficient automated human sleep analysis systems is the development of reliable pre-processing tools to discriminate between outlier/artifact instances and data of interest. This paper investigates the application of an automated approach, using the generalized singular value decomposition algorithm, to compensate for specific psg artifacts.