Jansen B H, Shankar K
Department of Electrical Engineering and Bioengineering Research Center, University of Houston, TX 77204-4793.
Int J Biomed Comput. 1993 May;32(3-4):289-97. doi: 10.1016/0020-7101(93)90021-w.
Body movement related signals (i.e., activity due to postural changes and the ballistocardiac effort) were recorded from six normal volunteers using the static-charge-sensitive bed (SCSB). Visual sleep staging was performed on the basis of simultaneously recorded EEG, EMG and EOG signals. A statistical classification technique was used to determine if reliable sleep staging could be performed using only the SCSB signal. A classification rate of between 52% and 75% was obtained for sleep staging in the five conventional sleep stages and the awake state. These rates improved from 78% to 89% for classification between awake, REM and non-REM sleep and from 86% to 98% for awake versus asleep classification.
使用静电荷敏感床（SCSB）从六名正常志愿者身上记录与身体运动相关的信号（即由于姿势变化和心冲击运动产生的活动）。基于同时记录的脑电图（EEG）、肌电图（EMG）和眼电图（EOG）信号进行视觉睡眠分期。使用一种统计分类技术来确定仅使用SCSB信号是否可以进行可靠的睡眠分期。在五个传统睡眠阶段和清醒状态下进行睡眠分期时，分类率在52%至75%之间。对于清醒、快速眼动（REM）睡眠和非快速眼动（non-REM）睡眠之间的分类，这些比率从78%提高到89%，对于清醒与睡眠的分类，比率从86%提高到98%。
