基于小波变换的脑电图α波持续性的研究
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摘要
随着科学技术的发展和人类社会的进步,人类从对自然的研究发展到对社会的研究,又发展到对人脑思维的研究,而脑电的信息处理研究正是这方面的典型领域。小波分析作为一种新的多分辨率分析方法,以其优良的特性和成熟的分析方法在国外的医学、心理学和认知神经科学研究中已被广泛使用。
意义:α波是确定脑电信号快慢的基准波,具有很多重要的生理意义,与年龄的关系很早前就被发现了。许多研究结果证明α波还与记忆力,认知能力,信息处理等多种脑机能有关,并可以作为情绪表现的指标。小波分析的一个重要特点就是具有良好的时频局部化性质,对于处理这种时变信号具有独特的优越性。因此运用小波分析来观察EEG信号中的α波在不同刺激事件下的持续性变化是非常有意义的。
方法:本研究主要是利用Morlet小波变换来获取EEG信号中α波随时间变化的能量分布,并在此基础上获取α波的持续时间。本研究设计了两个实验:心算、音乐,目的是观察α波在大脑进行信息计算和音乐信息处理时的变化趋势。最后根据两个实验所采集的脑电数据进行分析和计算,进而对α波的持续性和脑机能的关系做更深层的分析。
结论:通过对实验数据的计算和分析,可以得出以下结论:在心算时男性左半球α波受到抑制,听音乐时则右半球的α波受到抑制,而女性则没有这种明显左右差异。说明男性半球优势较女性更为显著。无论男性和女性在听音乐时,顶枕部的α波都更加活跃,说明音乐非常有助于提升α波,安静放松时听音乐对人类大脑是十分有益处的。另外在听不喜欢音乐和喜欢音乐的时候α波的持续时间是不一样的,由此可以看出个人喜好对于α波持续性的影响也不容忽视,个人喜好的音乐更加有益于提升α波。
With the development of scientific technological and progress of human society, the study of mankind is from the nature development to the society, but also developed into the study of human brain thinking, and the information processing of EEG is the typical areas. Wavelet analysis is a new multi-resolution analysis methods, it has been widely used in research of medicine, psychology and cognitive neuroscience with its excellent features and sophisticated analytical method.
Significance: Alpha wave is the base wave which determined the speed of EEG, it has many important physiological significance. The relationship with age was discovered much earlier, many studies have proved that a wave has related to memory, cognitive ability, information processing and other functions of brain, and can be used as indicators of emotional performance. An important feature of wavelet analysis is to have a good time-frequency localization properties, dealing with such time-varying signal has a unique advantage. Therefore, it has observed that alpha wave's continuity of change under different stimulus events is very meaningful.
Methods: This article explains how to use the Morlet wavelet transform to obtain EEG’s alpha wave energy distribution over time, and according to the EEG data of mental arithmetic and hearing music experiment to obtain the changes of the alpha wave duration. This study was designed two experiments: mental arithmetic, music, the purpose is to observe the trend of the brain’s alpha wave in information computing and information processing of music, Then do a more deep analysis of the relationship between alpha wave’s continuous and the brain’s function.
Conclusion: Through calculation and analysis of experimental data, we can draw the following conclusions: During the experiment of mental arithmetic, male’s alpha wave of left hemisphere is suppressed; when listening to music the alpha wave of the right hemisphere is suppressed, while women are no obvious bias, indicated that men’s hemispheric dominance more pronounced than women. In listening to music, both male and female’s alpha waves are more active, indicated that listen to music is very helpful to alpha wave and listening to music is very beneficial for the brain. In addition listening to unlike and like music of the alpha wave’s duration is differently, so we can see that personal preference has large impact for sustainability of alpha wave and listening to liked music is more beneficial to alpha wave.
意义:α波是确定脑电信号快慢的基准波,具有很多重要的生理意义,与年龄的关系很早前就被发现了。许多研究结果证明α波还与记忆力,认知能力,信息处理等多种脑机能有关,并可以作为情绪表现的指标。小波分析的一个重要特点就是具有良好的时频局部化性质,对于处理这种时变信号具有独特的优越性。因此运用小波分析来观察EEG信号中的α波在不同刺激事件下的持续性变化是非常有意义的。
方法:本研究主要是利用Morlet小波变换来获取EEG信号中α波随时间变化的能量分布,并在此基础上获取α波的持续时间。本研究设计了两个实验:心算、音乐,目的是观察α波在大脑进行信息计算和音乐信息处理时的变化趋势。最后根据两个实验所采集的脑电数据进行分析和计算,进而对α波的持续性和脑机能的关系做更深层的分析。
结论:通过对实验数据的计算和分析,可以得出以下结论:在心算时男性左半球α波受到抑制,听音乐时则右半球的α波受到抑制,而女性则没有这种明显左右差异。说明男性半球优势较女性更为显著。无论男性和女性在听音乐时,顶枕部的α波都更加活跃,说明音乐非常有助于提升α波,安静放松时听音乐对人类大脑是十分有益处的。另外在听不喜欢音乐和喜欢音乐的时候α波的持续时间是不一样的,由此可以看出个人喜好对于α波持续性的影响也不容忽视,个人喜好的音乐更加有益于提升α波。
With the development of scientific technological and progress of human society, the study of mankind is from the nature development to the society, but also developed into the study of human brain thinking, and the information processing of EEG is the typical areas. Wavelet analysis is a new multi-resolution analysis methods, it has been widely used in research of medicine, psychology and cognitive neuroscience with its excellent features and sophisticated analytical method.
Significance: Alpha wave is the base wave which determined the speed of EEG, it has many important physiological significance. The relationship with age was discovered much earlier, many studies have proved that a wave has related to memory, cognitive ability, information processing and other functions of brain, and can be used as indicators of emotional performance. An important feature of wavelet analysis is to have a good time-frequency localization properties, dealing with such time-varying signal has a unique advantage. Therefore, it has observed that alpha wave's continuity of change under different stimulus events is very meaningful.
Methods: This article explains how to use the Morlet wavelet transform to obtain EEG’s alpha wave energy distribution over time, and according to the EEG data of mental arithmetic and hearing music experiment to obtain the changes of the alpha wave duration. This study was designed two experiments: mental arithmetic, music, the purpose is to observe the trend of the brain’s alpha wave in information computing and information processing of music, Then do a more deep analysis of the relationship between alpha wave’s continuous and the brain’s function.
Conclusion: Through calculation and analysis of experimental data, we can draw the following conclusions: During the experiment of mental arithmetic, male’s alpha wave of left hemisphere is suppressed; when listening to music the alpha wave of the right hemisphere is suppressed, while women are no obvious bias, indicated that men’s hemispheric dominance more pronounced than women. In listening to music, both male and female’s alpha waves are more active, indicated that listen to music is very helpful to alpha wave and listening to music is very beneficial for the brain. In addition listening to unlike and like music of the alpha wave’s duration is differently, so we can see that personal preference has large impact for sustainability of alpha wave and listening to liked music is more beneficial to alpha wave.
引文
[1] (日)大熊辉雄著;周锦华译.临床脑电图学(第5版)[M].北京:清华大学出版社,2005:64-112.
[2] Astrid von S, Johannes S.Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization[J] : International Journal of Psychophysiology, 2000,38:301-313.
[3] S.Blanco, Blanco S, Kochen S,et al.Applying time-frequency analysis to seizure EEG activity[J]:IEEE Engineering in medicine and biology magazine, 1997,16:65-71
[4] Walter J, Gonzalo V, Di P.Relation of Olfactory EEG to Behavior: Time Series Analysis[J]:Behavioral Neuroscience, 1986,100:753-763.
[5] Rosso OA, Blanco S, Yordanova J, et al.Wavelet entropy: a new tool for analysis of short duration brain electrical signals[J]:Neurosci Methods, 2001,105:65–75.
[6] Blanco S, Figliola A, Quiroga RQ, et al.Time–frequency analysis of electroencephalogram series(III):wavelet packets and information cost function[J]:Physical Review E.1998, 57:932–940.
[7]赵晶晶,牟书,舒华,王春茂.基于Morlet小波变换的EEG时频分析[J]:中国医学物理学杂志,2006,23:56-59
[8] Petsche H, Kaplan S, Von Stein A, et al.The possible meaning of the upper and lower alpha frequency ranges for cognitive and creative tasks[J] : International Journal of Psychophysiology, 1997,26:77-97.
[9] Kawasaki M, Karashima M, Saito M.Effect of emotional changes induced by sounds on human frontal alpha-wave during verbal and non-verbal tasks [J]:International Journal of Biomedical Engineering and Technology, 2009,3:199-202.
[10] Enrique O, Flores G, Jose L D, et al.Differential alpha coherence hemispheric patterns in men and women during pleasant and unpleasant musical emotions[J]:International Journal of Psychophysiology, 2009:43-49
[11] Silva L, Leeuwen S.The cortical source of alpha rhythm [J]:Neurosci Lett, 1977,6:237-241
[12] Rodriguez E, George N, Lachaux J, et al.Perception’s shadow: long-distance synchronization of human brain activity[J]:Nature, 1999,397 (6718):430-433.
[13]曹河,沃建中,林崇德,等.6-12岁儿童脑电α波频率分布特点与信息加工速度的关系[J]:心理学探新,2004,20:131-134.
[14]沃建中,林崇德,潘显.13一18岁青少年脑电α波的发展特点[J]:北京师范大学学报(自然科学版),2001,6:78-81.
[15]马妍妍,李寿欣.个体智力差异的脑电生理学基础——来自EEG和ERP的证据[J]:心理科学进展2007,15(6):872-877.
[16] Tiihonen J, Hari R, Kajola M, et al.Magnetoencephalographic 10-Hz rhythm from the human auditory cortex[J]:Neurosci Lett, 1991,129:303-305
[17] James A, Coan J, Allen J.Frontal EEG asymmetry as a moderator and mediator of emotion[J]:Biological Psychology, 2004,67:7–49
[18] Kristin A, Jessica R, Isa D, et al.Right Frontal Brain Activity, Cortisol, and Withdrawal Behavior in 6-Month-Old Infants[J]:Behavioral Neuroscience, 2003, Vol. 117(1), 11-20
[19] Bas E, Basar-Erogluc C, Karakas S.Gamma alpha delta and theta oscillations govern cognitive processes[J]:International Journal of Psychophysiology, 2001,39 :241-248
[20] van Winsum W, Sergeant J, Gueze R..The functional signifcance of eventrelated desynchronization of alpha rhythms in attentional and activating tasks[J]:Electroenceph clin Neurophysiol, 1984, 58:519-524
[21] Westphal KP, GroEzinger B, Diekmann V, et al.EEG-blocking before and during voluntary movements: differences between the eyesclosed and eyes-open condition[J] : Arch Ital Biol, 1993,131:25-35
[22]季忠,秦树人.Wigner分布在脑电信号中的应用.信号处理,2002,18(6):570-573.
[23]孟欣,欧阳楷.脑电信号的几个非线性动力学分析方法.北京生物医学工程,1997,16(3):135-141.
[24] Senhagji L, Wendling F.Epileptic transient detection: wavelets and time frequency approaches[J]:Clin Neurophysiology,2002,32.
[25]飞思科技产品研发中心.小波分析理论与MATLAB7实现[M].北京:电子工业出版社,2005:9-83.
[26]李弼程,罗建书.小波分析及其应用.北京:电子工业出版社,2003:200-236.
[27]季中.脑电信息提取的时频分析方法式脑电图仪的研制.重庆大学,2003:14-16
[28] Samar V J, Bopardikar A, Rao R, et al.Wavelet Analysis of neuroelectric waveforms:A Conceptual Tutorial [J]:Brain and Language, 1999,66:2-5.
[29] Saab R, Mckeown M J, Myers L J,et al.Wavelet Based Approach for the Detection of Coupling in EEG Signals [J]:Proceedings of the 2 International IEEE EMBS Conference on Neural Engineering, 2005, March:16-19.
[30] Torrence C, Compo G P.A practical guide to wavelet analysis Bull[J]:Am Meteorl Soc, 1998,79:61–78.
[31] Pfurtscheller G, Lopes D Silva FH.Event-related EEG/MEG synchronization and desynchronization: basic principles[J]:Clinical Neurophysiology, 1999,110:1842-1857.
[32] Klimesch W . EEG-alpha rhythms and memory processes[J] : International Journal of Psychophysiology, 1997,26:319-340.
[33] Shizue K, Toshio K.Evaluation of Work Stress Using Psychological and Physiological Measures of Mental Activity in a Paced Calculating Task[J]:Industrial Health, 1995,33:7-22.
[34] Fumikazu M, Eduardo M.EEG data into space-time-frequency components using Parallel Factor Analysis[J]:NeuroImage, 2004, 22:1035–1045
[35] Maria H, Miguel D, Tiffany F.Instrumental and vocal music effects on EEG and EKG in neonates of depressed and non-depressed mothers[J]:Infant Behavior and Development, 2006,29:518-525
[36] Sylvie C, Marie-Eve B, Constant R, et al.Correlation between evening and morning waking EEG and spatial orientation[J]:Brain and Cognition, 2003,53:162-165.
[37] Eulitz C, Maess B, Antev C, et al.Oscillatory neuromagnetie activity induced by language and non—language stimuli[J]:Cognitive Brain Research, 1996,4:l2l—l32.
[38] Merzagora C, Bunce S, Izzetoglu M, et al.Wavelet analysis for EEG feature extraction in deception detection[J]:Proceedings of the 28th IEEE EMBS Annual International Conference New York City, Aug 30-Sept 3, 2006
[39] Hammond K, Whit R.The analysis of the non-stationary signals using time frequency methods[J]: Journal of Sound and Vibration, 1996,190(3):419--447.
[40] Jiruska P, Sovka P, Marusic P, et al.Comparison of Different Methods of Time Shift Measurement in EEG[J]:Physiol.Res, 2005,54:459-465.
[2] Astrid von S, Johannes S.Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization[J] : International Journal of Psychophysiology, 2000,38:301-313.
[3] S.Blanco, Blanco S, Kochen S,et al.Applying time-frequency analysis to seizure EEG activity[J]:IEEE Engineering in medicine and biology magazine, 1997,16:65-71
[4] Walter J, Gonzalo V, Di P.Relation of Olfactory EEG to Behavior: Time Series Analysis[J]:Behavioral Neuroscience, 1986,100:753-763.
[5] Rosso OA, Blanco S, Yordanova J, et al.Wavelet entropy: a new tool for analysis of short duration brain electrical signals[J]:Neurosci Methods, 2001,105:65–75.
[6] Blanco S, Figliola A, Quiroga RQ, et al.Time–frequency analysis of electroencephalogram series(III):wavelet packets and information cost function[J]:Physical Review E.1998, 57:932–940.
[7]赵晶晶,牟书,舒华,王春茂.基于Morlet小波变换的EEG时频分析[J]:中国医学物理学杂志,2006,23:56-59
[8] Petsche H, Kaplan S, Von Stein A, et al.The possible meaning of the upper and lower alpha frequency ranges for cognitive and creative tasks[J] : International Journal of Psychophysiology, 1997,26:77-97.
[9] Kawasaki M, Karashima M, Saito M.Effect of emotional changes induced by sounds on human frontal alpha-wave during verbal and non-verbal tasks [J]:International Journal of Biomedical Engineering and Technology, 2009,3:199-202.
[10] Enrique O, Flores G, Jose L D, et al.Differential alpha coherence hemispheric patterns in men and women during pleasant and unpleasant musical emotions[J]:International Journal of Psychophysiology, 2009:43-49
[11] Silva L, Leeuwen S.The cortical source of alpha rhythm [J]:Neurosci Lett, 1977,6:237-241
[12] Rodriguez E, George N, Lachaux J, et al.Perception’s shadow: long-distance synchronization of human brain activity[J]:Nature, 1999,397 (6718):430-433.
[13]曹河,沃建中,林崇德,等.6-12岁儿童脑电α波频率分布特点与信息加工速度的关系[J]:心理学探新,2004,20:131-134.
[14]沃建中,林崇德,潘显.13一18岁青少年脑电α波的发展特点[J]:北京师范大学学报(自然科学版),2001,6:78-81.
[15]马妍妍,李寿欣.个体智力差异的脑电生理学基础——来自EEG和ERP的证据[J]:心理科学进展2007,15(6):872-877.
[16] Tiihonen J, Hari R, Kajola M, et al.Magnetoencephalographic 10-Hz rhythm from the human auditory cortex[J]:Neurosci Lett, 1991,129:303-305
[17] James A, Coan J, Allen J.Frontal EEG asymmetry as a moderator and mediator of emotion[J]:Biological Psychology, 2004,67:7–49
[18] Kristin A, Jessica R, Isa D, et al.Right Frontal Brain Activity, Cortisol, and Withdrawal Behavior in 6-Month-Old Infants[J]:Behavioral Neuroscience, 2003, Vol. 117(1), 11-20
[19] Bas E, Basar-Erogluc C, Karakas S.Gamma alpha delta and theta oscillations govern cognitive processes[J]:International Journal of Psychophysiology, 2001,39 :241-248
[20] van Winsum W, Sergeant J, Gueze R..The functional signifcance of eventrelated desynchronization of alpha rhythms in attentional and activating tasks[J]:Electroenceph clin Neurophysiol, 1984, 58:519-524
[21] Westphal KP, GroEzinger B, Diekmann V, et al.EEG-blocking before and during voluntary movements: differences between the eyesclosed and eyes-open condition[J] : Arch Ital Biol, 1993,131:25-35
[22]季忠,秦树人.Wigner分布在脑电信号中的应用.信号处理,2002,18(6):570-573.
[23]孟欣,欧阳楷.脑电信号的几个非线性动力学分析方法.北京生物医学工程,1997,16(3):135-141.
[24] Senhagji L, Wendling F.Epileptic transient detection: wavelets and time frequency approaches[J]:Clin Neurophysiology,2002,32.
[25]飞思科技产品研发中心.小波分析理论与MATLAB7实现[M].北京:电子工业出版社,2005:9-83.
[26]李弼程,罗建书.小波分析及其应用.北京:电子工业出版社,2003:200-236.
[27]季中.脑电信息提取的时频分析方法式脑电图仪的研制.重庆大学,2003:14-16
[28] Samar V J, Bopardikar A, Rao R, et al.Wavelet Analysis of neuroelectric waveforms:A Conceptual Tutorial [J]:Brain and Language, 1999,66:2-5.
[29] Saab R, Mckeown M J, Myers L J,et al.Wavelet Based Approach for the Detection of Coupling in EEG Signals [J]:Proceedings of the 2 International IEEE EMBS Conference on Neural Engineering, 2005, March:16-19.
[30] Torrence C, Compo G P.A practical guide to wavelet analysis Bull[J]:Am Meteorl Soc, 1998,79:61–78.
[31] Pfurtscheller G, Lopes D Silva FH.Event-related EEG/MEG synchronization and desynchronization: basic principles[J]:Clinical Neurophysiology, 1999,110:1842-1857.
[32] Klimesch W . EEG-alpha rhythms and memory processes[J] : International Journal of Psychophysiology, 1997,26:319-340.
[33] Shizue K, Toshio K.Evaluation of Work Stress Using Psychological and Physiological Measures of Mental Activity in a Paced Calculating Task[J]:Industrial Health, 1995,33:7-22.
[34] Fumikazu M, Eduardo M.EEG data into space-time-frequency components using Parallel Factor Analysis[J]:NeuroImage, 2004, 22:1035–1045
[35] Maria H, Miguel D, Tiffany F.Instrumental and vocal music effects on EEG and EKG in neonates of depressed and non-depressed mothers[J]:Infant Behavior and Development, 2006,29:518-525
[36] Sylvie C, Marie-Eve B, Constant R, et al.Correlation between evening and morning waking EEG and spatial orientation[J]:Brain and Cognition, 2003,53:162-165.
[37] Eulitz C, Maess B, Antev C, et al.Oscillatory neuromagnetie activity induced by language and non—language stimuli[J]:Cognitive Brain Research, 1996,4:l2l—l32.
[38] Merzagora C, Bunce S, Izzetoglu M, et al.Wavelet analysis for EEG feature extraction in deception detection[J]:Proceedings of the 28th IEEE EMBS Annual International Conference New York City, Aug 30-Sept 3, 2006
[39] Hammond K, Whit R.The analysis of the non-stationary signals using time frequency methods[J]: Journal of Sound and Vibration, 1996,190(3):419--447.
[40] Jiruska P, Sovka P, Marusic P, et al.Comparison of Different Methods of Time Shift Measurement in EEG[J]:Physiol.Res, 2005,54:459-465.