Automated determination of wakefulness and sleep in rats based on non-invasively acquired measures of movement and respiratory activity.
Automated determination of wakefulness and sleep in rats based on non-invasively acquired measures of movement and respiratory activity.
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DOI：
10.1016/j.jneumeth.2011.12.001
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发表时间：
2012-03-15
影响因子：
3
通讯作者：
Sanford, Larry D.
中科院分区：
文献类型：
--
作者：
Zeng, Tao;Mott, Christopher;Mollicone, Daniel;Sanford, Larry D.
关键词：
目前监测大鼠睡眠的标准需要劳动密集型外科手术和植入慢性电极，这些电极可能会影响行为和睡眠。为了开发一种非侵入性方法来确定睡眠和觉醒，我们构建了一个非接触式监测系统，使用脉冲多普勒雷达和数字化视频分析获得的信号来测量运动和呼吸活动。一组23个频率和时域特征来自这些信号，并在10秒的历元计算。基于这些特征，使用支持向量机（SVM）开发了一种用于大鼠觉醒、非快速眼动睡眠（NREM）和REM自动评分的分类方法。然后，我们通过将结果与基于同时记录的EEG和EMG的觉醒和睡眠的标准评分进行比较，评估了自动评分系统在区分觉醒和睡眠方面的实用性。基于所选特征的SVM自动评分与基于EEG和EMG的视觉评分之间的一致性对于觉醒约为91%，对于NREM约为84%，对于REM约为70%。结果表明，基于非侵入性获得的运动和呼吸活动的自动评分将有助于需要区分觉醒和睡眠的研究。然而，需要额外的信息或信号来改善睡眠中NREM和REM发作的区分。
The current standard for monitoring sleep in rats requires labor intensive surgical procedures and the implantation of chronic electrodes which have the potential to impact behavior and sleep. With the goal of developing a non-invasive method to determine sleep and wakefulness, we constructed a non-contact monitoring system to measure movement and respiratory activity using signals acquired with pulse Doppler radar and from digitized video analysis. A set of 23 frequency and time-domain features were derived from these signals and were calculated in 10 s epochs. Based on these features, a classification method for automated scoring of wakefulness, non-rapid eye movement sleep (NREM) and REM in rats was developed using a support vector machine (SVM). We then assessed the utility of the automated scoring system in discriminating wakefulness and sleep by comparing the results to standard scoring of wakefulness and sleep based on concurrently recorded EEG and EMG. Agreement between SVM automated scoring based on selected features and visual scores based on EEG and EMG were approximately 91% for wakefulness, 84% for NREM and 70% for REM. The results indicate that automated scoring based on non-invasively acquired movement and respiratory activity will be useful for studies requiring discrimination of wakefulness and sleep. However, additional information or signals will be needed to improve discrimination of NREM and REM episodes within sleep.
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影响因子：
4.3
作者：
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通讯作者：
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DOI：
10.1109/tmtt.2004.823552
发表时间：
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影响因子：
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