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为了研究疼痛暴露对新生儿自主神经系统的影响,并建立基于心率变异性(heart rate variability,HRV)指标的新生儿疼痛检测模型,采用时域、频域和非线性方法对40名新生儿疼痛暴露前后的心电数据进行短时HRV分析,Wilcoxon符号秩检验用于统计分析,支持向量机(support vector machine,SVM)用于建立检测模型. 结果表明,RR间期均值aRR、低频段功率LF、高频段功率HF等3个线性指标和近似熵ApEn、样本熵SampEn、递归率REC等9个非线性指标在疼痛前后具有统计学差异;基于aRR、相邻两个RR间期对差值大于50 ms的百分比pNN50,ApEn,关联维D2和REC等5个指标和SVM的疼痛检测模型检测正确率达到83.75%. HRV的相关指标可反映新生儿自主神经系统对疼痛暴露的应答,基于HRV指标和SVM 的模型可用于新生儿疼痛检测.To investigate the influence of pain exposure on autonomic nervous system of newborns, and develop a detection model based on heart rate variability (HRV) indexes, 40 newborns are recruited in the study and short-term HRV analyses are performed on electrocardiogram before and after pain exposure using time-domain, frequency domain and nonlinear methods. Wilcoxon signed rank test is adopted for statistical comparison, and the support vector machine (SVM) is used for developing a detection model. The results demonstrate that 3 linear indexes such as the mean of RR intervals aRR, absolute powers of low frequency band LF and absolute powers of high frequency band HF, and 9 nonlinear indexes such as approximate entropy ApEn, sample entropy SampEn, and determinism DET before pain exposure are significantly different from after pain exposure; and that a detection accuracy of 83.75% could be achieved by the model based on the combination of 5 indexes, i.e., aRR, proportion of adjacent intervals greater than 50 ms pNN50, ApEn, correlation dimension D2 and recurrence rate REC, and SVM. It suggests that HRV indexes can reveal the response of autonomous nervous system to pain exposure of newborns, and the model based on HRV indexes and SVM could be employed for the detection of pain.
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Keywords:
- heart rate variability /
- newborns /
- pain /
- support vector machine
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[19] Sokolova M, Lapalme G 2009 Inform. Process. Managem. 45 427
[20] Oberlander T F, Grunau R E, Whitfield M F, Fitzgerald C, Pitfield S, Saul J P 2000 Pediatrics 105 e6
[21] Ding L J, Peng H, Cai S M, Zhou P L 2007 Chin. Phys. Lett. 24 2149
[22] Peng C K, Havlin S, Stanley H E, Goldberger A L 1995 Chaos 5 82
[23] Melillo P, Bracale M, Pecchia L 2011 Biomed. Engineer. Online 10 96
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[1] Weissman A, Aranovitch M, Blazer S, Zimmer E Z 2009 Pediatrics 128 e921
[2] Jiang L, Li H 2012 Chin. J. Neonatol. 27 289 (in Chinese) [蒋犁, 李函 2012 中国新生儿科杂志 27 289]
[3] Faye P M, De Jonckheere J, Logier R, Kuissi E, Jeanne M, Rakza T, Storme L 2010 Clinical J. Pain 26 777
[4] Yoo C S, Yi S H 2004 J. Korean Phys. Soc. 44 561
[5] Li J, Liu D Z 2012 Acta Phys. Sin. 61 208701 (in Chinese) [李锦, 刘大钊 2012 物理学报 61 208701]
[6] Zhuang J J, Ning X B, Zou M, Sun B, Yang X 2008 Acta Phys. Sin. 57 2805 (in Chinese) [庄建军, 宁新宝, 邹鸣, 孙飙, 杨希 2008 物理学报 57 2805]
[7] Weissman A, Zimmer E Z, Aranovitch M 2012 Pflug. Archiv-European J. Physiol. 464 593
[8] Huo C Y, Zhuang J J, Huang X L, Hou F Z, Ning X B 2012 Acta Phys. Sin. 61 190506 (in Chinese) [霍铖宇, 庄建军, 黄晓林, 侯凤贞, 宁新宝 2012 物理学报 61 190506]
[9] Peng C K, Havlin S, Stanley H E 1995 Chaos 5 82
[10] Tang Y F, Liu S L, Jiang R H, Liu Y H 2013 Chin. Phys. B 22 030504
[11] Webber C L, Zbilut J P 1994 J. Appl. Physiol. 76 965
[12] Eckmann J P, Kamphorst S O, Ruelle D 1987 Europhys. Lett. 4 973
[13] Richman J S, Moorman J R 2000 Am. J. Physiol.: Heart and Circulat. Physiol. 278 H2039
[14] Cao B, Xiang Y P, L X Q, Zeng M, Huang S S 2008 Chin. Phys. B 17 865
[15] Grassberger P, Procaccia I 1983 Phys. Rev. Lett. 50 346
[16] Wang J S, Yuan J, Li Q, Yuan R X 2011 Chin. Phys. B 20 050506
[17] Wang G S, Zhong Y X 2001 Acta Electron. Sin. 10 1397 (in Chinese) [王国胜, 钟义信 2001 电子学报 10 1397]
[18] Chang C C, Lin C J 2011 ACM Trans. Intellig. Syst. Technol. 2 27
[19] Sokolova M, Lapalme G 2009 Inform. Process. Managem. 45 427
[20] Oberlander T F, Grunau R E, Whitfield M F, Fitzgerald C, Pitfield S, Saul J P 2000 Pediatrics 105 e6
[21] Ding L J, Peng H, Cai S M, Zhou P L 2007 Chin. Phys. Lett. 24 2149
[22] Peng C K, Havlin S, Stanley H E, Goldberger A L 1995 Chaos 5 82
[23] Melillo P, Bracale M, Pecchia L 2011 Biomed. Engineer. Online 10 96
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