To dig the sleep-related breathing events information in R- R Intervals and advance the technology for nonintrusive monitoring. By using of wavelet analysis method the feature waves related with breathing events was fetched by decomposing and reconstructing the R - R intervals signals from patients with SAHS (sleep apnea hypopnea syndrome) whole night. The relationship between the feature waves and breathing events was studied, and by which the position and type of breathing events were distinguished. The distinguished result compared with that of polysomnograph showed that the proposed method was effective and practicable.%为了挖据心动周期中的睡眠呼吸事件信息,为无干扰睡眠呼吸事件监测提供技术支持,本文利用多分辨率小波分析方法,对患有睡眠呼吸暂停低通气综合征病人的心率序列进行分解和重建,获得与睡眠呼吸事件相关联的特征波形.根据特征波形的波形特点与睡眠呼吸事件的关系,最后识别出呼吸事件发生的位置和类型.上述方法的分析结果与多功能睡眠记录仪结果进行比较证实该方法是有效和可行的.
展开▼
