新生儿脑电图-睡眠分期及其应用_Journal of Epilepsy

Authors：

王晓璐 ,  江军 , 匡光涛 , 刘垚玲

武汉市儿童医院·武汉市妇女儿童医疗保健中心脑电图室(武汉 430016);

Corresponding author：

江军, Email: jiangjunzm@163.com

Keywords：

新生儿; 定量脑电图; 睡眠分期; 癫痫发作

DOI：

10.7507/2096-0247.20170085

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

近年来新生儿脑电图(EEG)对于评估脑功能的作用被逐渐认可，并在国内越来越多的医院开展，一般结果由医师阅图后凭经验主观判断，仅依靠定性EEG。而随着定量EEG研究的增多，依靠客观数据处理实现新生儿睡眠自动分期得以实现，并可以自动检出新生儿癫痫发作的时间段，节省人工阅图时间，辅助医师对结果做出判断。EEG-睡眠分期的分析应用广泛, 可以帮助更准确的识别新生儿脑病，评估新生儿神经功能和脑成熟度，提供一种研究新生儿大脑发育成熟的机制的方法。

Citation： 王晓璐, 江军, 匡光涛, 刘垚玲. 新生儿脑电图-睡眠分期及其应用. Journal of Epilepsy, 2017, 3(6): 522-524. doi: 10.7507/2096-0247.20170085 Copy

1.	吴至凤, 邓虹燕, 李骁.睡眠影响婴幼儿认知发育的机制研究.癫痫杂志, 2017, 3(4): 329-332.
2.	Piryatinska A, Terdik G, Woyczynski WA, et al. Automated detection of neonate EEG sleep stages. Comput Methods Programs Biomed, 2009, 95(1): 31-46.
3.	Fraiwan L, Lweesy K, Khasawneh N, et al. Time frequency analysis for automated sleep stage identification in fullterm and preterm neonates. J Med Syst, 2011, 35(4): 693-702.
4.	O'Toole JM, Boylan GB, Vanhatalo S, et al. Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram. Clin Neurophysiol, 2016, 127(8): 2910-2918.
5.	Boashash B, Ouelha S. Automatic signal abnormality detection using time-frequency features and machine learning. Knowl-Based Syst, 2016, 106(8): 38-50.
6.	Scher MS, Steppe DA, Beggarly ME, et al. Neonatal EEG-sleep disruption mimicking hypoxic-ischemic encephalopathy after intrapartum asphyxia. Sleep Med, 2002, 3(5): 411-415.
7.	Shellhaas RA, Burns JW, Barks JD, et al. Quantitative sleep stage analyses as a window to neonatal neurologic function. Neurology, 2014, 82(5): 390-395.
8.	Scher MS, Jones BL, Steppe DA, et al. Functional brain maturation in neonates as measured by EEG-sleep analyses. Clin Neurophysiol, 2003, 114(5): 875-882.
9.	Nunes ML, Da CJ. Sleep and epilepsy in neonates. Sleep Med, 2010, 11(7): 665-673.

1. 吴至凤, 邓虹燕, 李骁.睡眠影响婴幼儿认知发育的机制研究.癫痫杂志, 2017, 3(4): 329-332.
2. Piryatinska A, Terdik G, Woyczynski WA, et al. Automated detection of neonate EEG sleep stages. Comput Methods Programs Biomed, 2009, 95(1): 31-46.
3. Fraiwan L, Lweesy K, Khasawneh N, et al. Time frequency analysis for automated sleep stage identification in fullterm and preterm neonates. J Med Syst, 2011, 35(4): 693-702.
4. O'Toole JM, Boylan GB, Vanhatalo S, et al. Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram. Clin Neurophysiol, 2016, 127(8): 2910-2918.
5. Boashash B, Ouelha S. Automatic signal abnormality detection using time-frequency features and machine learning. Knowl-Based Syst, 2016, 106(8): 38-50.
6. Scher MS, Steppe DA, Beggarly ME, et al. Neonatal EEG-sleep disruption mimicking hypoxic-ischemic encephalopathy after intrapartum asphyxia. Sleep Med, 2002, 3(5): 411-415.
7. Shellhaas RA, Burns JW, Barks JD, et al. Quantitative sleep stage analyses as a window to neonatal neurologic function. Neurology, 2014, 82(5): 390-395.
8. Scher MS, Jones BL, Steppe DA, et al. Functional brain maturation in neonates as measured by EEG-sleep analyses. Clin Neurophysiol, 2003, 114(5): 875-882.
9. Nunes ML, Da CJ. Sleep and epilepsy in neonates. Sleep Med, 2010, 11(7): 665-673.

Previous Article
热性感染相关性癫痫综合征的诊治研究进展
Next Article
癫痫指南的目前状态：一项系统评价

Journal of Epilepsy

新生儿脑电图-睡眠分期及其应用

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content