基于单导脑电信号的在线压力监测系统研究与实现
摘要
社会经济的飞速发展使得人们面临的工作、生活和性格中的压力剧增。如何在进一步发展为精神紊乱病症之前,发现压力并及时采取措施是十分必要的。例如,压力的监测在检测和干预抑郁症过程中起到了关键的作用。
传统的压力监测手段是通过各种用户自评量表,但它的突出问题是难以避免的主观性。同时,缺乏一套可应用于日常生活中的压力监测系统。
为了能够在日常应用中准确客观的对压力进行监测,本文开发了一套在线压力监测系统。本系统通过采集Fpz一个电极的脑电信号,能够对用户的压力状态进行客观的评价并进行长期在线监测,同时可辅助医师对用户状态进行评估。系统采用c／s框架,基于soap协议,客户端分为用户界面和医师界面,用户界面包括信号采集、量表填写、历史记录查看、医师交互模块。医师界面包括查看用户历史记录和与用户交互模块。服务器端主要负责对用户数据进行有效管理,以及脑电信号的处理。
本文通过实验,选择出系统中使用的有效的脑电特征和算法。首先采集被试脑电信号,进行去噪、特征提取和分类,筛选出三个对压力分类有效地脑电信号特征(分别是LZ复杂度,alpha相对功率,alpha相对功率/beta相对功率),并通过结果对比最终确定K最近邻分类器为系统中的分类算法。为了直观的显示压力水平,引入了压力指数这一概念。
The rapid development of social economy makes people facing increasing stress from work, life and character. Before further development to mental disorder illness, how to detect the stress and take timely measures are very necessary. For example, the monitoring of the stress plays a key role in the process of detection and intervention of depression
The traditional mean of stress monitoring is a variety of user self-rating scale, but its outstanding problems is the difficulty of avoiding subjectivity. Meanwhile, we need an online stress monitoring system that can be applied in daily life.
In order to monitor stress easily and objectively in daily life, we build a pervasive online stress detection system. By collecting EEG from Fpz point, the system can make objective evaluation and conduct long-line monitoring of users' stress, at same time, can assist physicians to assess the users' state. Based soap protocol, the proposed system adopts client/server framework. Client-side consists of "User Panel" and "Doctor Panel". The "User Panel" integrates modules including biological signals acquisition, self-assessment questionnaire, history record and doctor chatting. The "Doctor Panel" includes history record module and user chatting panel. Server-side is mainly responsible for the effective management of users'data, as well as EEG processing.
For the purpose of adopting effective EEG features and algorithms in the system, an experiment has been conducted. After collecting subjects' EEG signal, denoising, feature extraction and classification, three features effective for stress classification were screened out, namely LZ-complexity, alpha relative power and the ratio of alpha power to beta power. By comparing results the k-nearest neighbor classifier were determined as classification algorithm in system. Meanwhile, we introduced the stress index for indicating stress level intuitionisticly.
传统的压力监测手段是通过各种用户自评量表,但它的突出问题是难以避免的主观性。同时,缺乏一套可应用于日常生活中的压力监测系统。
为了能够在日常应用中准确客观的对压力进行监测,本文开发了一套在线压力监测系统。本系统通过采集Fpz一个电极的脑电信号,能够对用户的压力状态进行客观的评价并进行长期在线监测,同时可辅助医师对用户状态进行评估。系统采用c／s框架,基于soap协议,客户端分为用户界面和医师界面,用户界面包括信号采集、量表填写、历史记录查看、医师交互模块。医师界面包括查看用户历史记录和与用户交互模块。服务器端主要负责对用户数据进行有效管理,以及脑电信号的处理。
本文通过实验,选择出系统中使用的有效的脑电特征和算法。首先采集被试脑电信号,进行去噪、特征提取和分类,筛选出三个对压力分类有效地脑电信号特征(分别是LZ复杂度,alpha相对功率,alpha相对功率/beta相对功率),并通过结果对比最终确定K最近邻分类器为系统中的分类算法。为了直观的显示压力水平,引入了压力指数这一概念。
The rapid development of social economy makes people facing increasing stress from work, life and character. Before further development to mental disorder illness, how to detect the stress and take timely measures are very necessary. For example, the monitoring of the stress plays a key role in the process of detection and intervention of depression
The traditional mean of stress monitoring is a variety of user self-rating scale, but its outstanding problems is the difficulty of avoiding subjectivity. Meanwhile, we need an online stress monitoring system that can be applied in daily life.
In order to monitor stress easily and objectively in daily life, we build a pervasive online stress detection system. By collecting EEG from Fpz point, the system can make objective evaluation and conduct long-line monitoring of users' stress, at same time, can assist physicians to assess the users' state. Based soap protocol, the proposed system adopts client/server framework. Client-side consists of "User Panel" and "Doctor Panel". The "User Panel" integrates modules including biological signals acquisition, self-assessment questionnaire, history record and doctor chatting. The "Doctor Panel" includes history record module and user chatting panel. Server-side is mainly responsible for the effective management of users'data, as well as EEG processing.
For the purpose of adopting effective EEG features and algorithms in the system, an experiment has been conducted. After collecting subjects' EEG signal, denoising, feature extraction and classification, three features effective for stress classification were screened out, namely LZ-complexity, alpha relative power and the ratio of alpha power to beta power. By comparing results the k-nearest neighbor classifier were determined as classification algorithm in system. Meanwhile, we introduced the stress index for indicating stress level intuitionisticly.
引文
[1]抑郁症.世界卫生组织实况报道,第369号2012年10月；Available from: http://www.who.int/mediacentre/factsheets/fs369/zh/index.html,
[2]Phillips M R, Zhang J, Shi Q, et al. Prevalence, treatment, and associated disability of mental disorders in four provinces in China during 2001-05:an epidemiological survey[J]. The Lancet,2009,373(9680):2041-2053.
[3]Greenberg P E, Birnbaum H G. The economic burden of depression in the US:societal and patient perspectives[J]. Expert opinion on pharmacotherapy,2005,6(3):369-376.
[4]韦盛中,张玲,杨丽.精神疾病负担的研究进展[J].中华行为医学与脑科学杂志,2010,19(5)：478-480.
[5]赵石.精神疾病,不可忽视的健康问题[J].科技致富向导.2013(1)：45-45.
[6]程明,任宇鹏,高小榕,等.脑电信号控制康复机器人的关键技术[J].机器人技术与应用,2003,4：45-48.
[7]Yan J Z, Hu B, Peng H, et al. An Ubiquitous Sleep Quality Monitoring and Evaluation[J].網降纲路技術学刊,2011,12(3)：375-381.
[8]Peng H, Hu B, Liu Q, et al. User-centered depression prevention:An EEG approach to pervasive healthcare[C]//Pervasive Computing Technologies for Healthcare (PervasiveHealth),2011 5th International Conference on. IEEE,2011:325-330.
[9]Seo S, Gil Y, Lee J. The effect of an auditory stressor, with respect to affective style, on frontal EEG asymmetry and ERP analysis[C]//Networked Computing and Advanced Information Management,2008. NCM'08. Fourth International Conference on. IEEE,2008,1: 662-667.
[10]Coan J A, Allen J J B. Frontal EEG asymmetry as a moderator and mediator of emotion[J]. Biological psychology,2004,67(1):7-50.
[11]刘建成,蔡湛宇.脑电信号(EEG)分析方法的现状与发展[J].中国医学物理学杂志,1998,15(4)：252-255.
[12]C.J.Stam,T.C.A.M van Woerkom,W.S.Pritchard. Use of non-linear EEG measures to characterize EEG changes during mental activity.Electroencephalography and clinical Neurophysiology.99(1996)214-224
[13]Ying-Jie Lee, Yi-Sheng Zhu, Yu-Hong Xu, Min-Fen Shen, Hong-Xuan Zhang, N.V.Thakor. Detection of non-linearity in the EEG of schizophrenic patients. Clinical Neurophysiology 112(2001)1288-1294
[14]Matsunami K, Homma S, Han X Y, et al. Generator Sources of EEG Large Waves Elicited by Mental Stress of Memory Recall or Mental Calculation[J]. The Japanese journal of physiology,2001,51(5):621-624.
[15]Lewis R S, Weekes N Y, Wang T H. The effect of a naturalistic stressor on frontal EEG asymmetry, stress, and health[J]. Biological psychology,2007,75(3):239-247.
[16]Tucker D M. Lateral brain function, emotion, and conceptualization[J]. Psychological bulletin,1981,89(1):19.
[17]Davidson R J, Schwartz G E. Saron C, et al. Frontal versus parietal EEG asymmetry during positive and negative affect[J]. Psychophysiology,1979,16(2):202-203.
[18]Davidson R J. Affective neuroscience and psychophysiology:Toward a synthesis[J]. Psychophysiology,2003,40(5):655-665.
[19]Davidson R J, Jackson D C, Kalin N H. Emotion, plasticity, context, and regulation: perspectives from affective neuroscience[J]. Psychological bulletin,2000,126(6):890.
[20]Davidson R J. Anterior cerebral asymmetry and the nature of emotion[J]. Brain and cognition,1992,20(1):125-151.
[21]Bierhaus A, Wolf J, Andrassy M, et al. A mechanism converting psychosocial stress into mononuclear cell activation[J]. Proceedings of the National Academy of Sciences,2003, 100(4):1920-1925.
[22]Epel E S, Blackburn E H, Lin J, et al. Accelerated telomere shortening in response to life stress[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004,101(49):17312-17315.
[23]Hosseini S A, Khalilzadeh M A. Emotional stress recognition system using EEG and psychophysiological signals:Using new labelling process of EEG signals in emotional stress state[C]//Biomedical Engineering and Computer Science (ICBECS),2010 International Conference on. IEEE,2010:1-6.
[24]Segerstrom S C, Miller G E. Psychological stress and the human immune system:a meta-analytic study of 30 years of inquiry[J]. Psychological bulletin,2004,130(4):601.
[25]Cohen S, Tyrrell D A J, Smith A P. Negative life events, perceived stress, negative affect, and susceptibility to the common cold[J]. Journal of personality and social psychology,1993, 64:131-131.
[26]Papousek I, Schulter G. Covariations of EEG asymmetries and emotional states indicate that activity at frontopolar locations is particularly affected by state factors[J]. Psychophysiology,2002,39(3):350-360.
[27]Hammen C. Stress and depression[J]. Annu. Rev. Clin. Psychol.,2005,1:293-319.
[28]McGonagle K A, Kessler R C. Chronic stress, acute stress, and depressive symptoms[J]. American Journal of Community Psychology,1990,18(5):681-706.
[29]Blackhart G C, Minnix J A, Kline J P. Can EEG asymmetry patterns predict future development of anxiety and depression?:A preliminary study[J]. Biological psychology, 2006,72(1):46-50.
[30]Li Y, Tong S, Liu D, et al. Abnormal EEG complexity in patients with schizophrenia and depression[J]. Clinical Neurophysiology,2008,119(6):1232-1241.
[31]Sulaiman N, Taib M N, Lias S, et al. EEG-based Stress Features Using Spectral Centroids Technique and k-Nearest Neighbor Classifier[C]//Computer Modelling and Simulation (UKSim),2011 UkSim 13th International Conference on. IEEE,2011:69-74.
[32]Fan X A, Bi L Z, Chen Z L. Using EEG to detect drivers'emotion with Bayesian Networks[C]//Machine Learning and Cybernetics (ICMLC),2010 International Conference on. IEEE.2010,3:1177-1181.
[33]Rani P, Sims J, Brackin R, et al. Online stress detection using psychophysiological signals for implicit human-robot cooperation[J], Robotica,2002,20(06):673-685.
[34]Peng H, Hu B, Qi Y, et al. An improved EEG de-noising approach in electroencephalogram (EEG) for home care[C]//Pervasive Computing Technologies for Healthcare (PervasiveHealth),2011 th International Conference on. IEEE,2011:469-474.
[35]RRNYI A. On measures of entropy and information[C]//Fourth Berkeley Symposium on Mathematical Statistics and Probability.1961:547-561.
[36]Lempel A, Ziv J. On the complexity of finite sequences[J]. Information Theory, IEEE Transactions on,1976,22(1):75-81.
[37]San-Ru H, Bo-Yu H, Xiao-Qiang X, et al. How to control a geometric quantum gatefJ]. Chinese Physics,2002,11(2):109.
[38]张佃中.非线性时间序列互信息与Lempel-Ziv复杂度的相关性研究[J].物理学报,2007，6.
[39]谢勇,徐健学,杨红军,等.皮层脑电时间序列的相空间重构及非线性特征量的提取[J].物理学报,2005,51(2)：205-214.
[40]洪时中.非线性时间序列分析的最新进展及其在地球科学中的应用前景[J].地球科学进展,1999,14(6)：559-565.
[41]Dian-Zhong Z. Research on the correlation between the mutual information and Lempel-Ziv complexity of nonlinear time series[].2007.
[42]陈芳,顾凡及,徐京华,刘增荣,刘仁.一种新的人脑信息传输复杂性的研究[J].生物物理学报,1998,14(3)：508-512
[43]Dharmawan Z. Analysis of computer games player stress level using EEG data[J]. Master of Science Thesis Report, Delft University of Technology, Netherlands,2007.
[44]Peng H, Hu B, Zheng F, et al. A method of identifying chronic stress by EEG[J]. Personal and Ubiquitous Computing,2012:1-7.
[45]Zhao W, Liu L, Zheng F, et al. Investigation into stress of mothers with mental retardation children based on EEG (electroencephalography) and psychology instruments[M]//Brain Informatics. Springer Berlin Heidelberg,2011:238-249.
[46]Pan W, Zhang L, Xia Y. The difference in EEG theta waves between concentrative and non-concentrative qigong states--a power spectrum and topographic mapping study[J]. Journal of traditional Chinese medicine= Chung i tsa chih ying wen pan/sponsored by All-China Association of Traditional Chinese Medicine, Academy of Traditional Chinese Medicine,1994,14(3):212.
[47]Bos D O. EEG-based emotion recognition[J]. The Influence of Visual and Auditory Stimuli,2006.
[48]Java RMI维基百科http://zh.wikipedia.org/wiki/Java RMI.
[2]Phillips M R, Zhang J, Shi Q, et al. Prevalence, treatment, and associated disability of mental disorders in four provinces in China during 2001-05:an epidemiological survey[J]. The Lancet,2009,373(9680):2041-2053.
[3]Greenberg P E, Birnbaum H G. The economic burden of depression in the US:societal and patient perspectives[J]. Expert opinion on pharmacotherapy,2005,6(3):369-376.
[4]韦盛中,张玲,杨丽.精神疾病负担的研究进展[J].中华行为医学与脑科学杂志,2010,19(5)：478-480.
[5]赵石.精神疾病,不可忽视的健康问题[J].科技致富向导.2013(1)：45-45.
[6]程明,任宇鹏,高小榕,等.脑电信号控制康复机器人的关键技术[J].机器人技术与应用,2003,4：45-48.
[7]Yan J Z, Hu B, Peng H, et al. An Ubiquitous Sleep Quality Monitoring and Evaluation[J].網降纲路技術学刊,2011,12(3)：375-381.
[8]Peng H, Hu B, Liu Q, et al. User-centered depression prevention:An EEG approach to pervasive healthcare[C]//Pervasive Computing Technologies for Healthcare (PervasiveHealth),2011 5th International Conference on. IEEE,2011:325-330.
[9]Seo S, Gil Y, Lee J. The effect of an auditory stressor, with respect to affective style, on frontal EEG asymmetry and ERP analysis[C]//Networked Computing and Advanced Information Management,2008. NCM'08. Fourth International Conference on. IEEE,2008,1: 662-667.
[10]Coan J A, Allen J J B. Frontal EEG asymmetry as a moderator and mediator of emotion[J]. Biological psychology,2004,67(1):7-50.
[11]刘建成,蔡湛宇.脑电信号(EEG)分析方法的现状与发展[J].中国医学物理学杂志,1998,15(4)：252-255.
[12]C.J.Stam,T.C.A.M van Woerkom,W.S.Pritchard. Use of non-linear EEG measures to characterize EEG changes during mental activity.Electroencephalography and clinical Neurophysiology.99(1996)214-224
[13]Ying-Jie Lee, Yi-Sheng Zhu, Yu-Hong Xu, Min-Fen Shen, Hong-Xuan Zhang, N.V.Thakor. Detection of non-linearity in the EEG of schizophrenic patients. Clinical Neurophysiology 112(2001)1288-1294
[14]Matsunami K, Homma S, Han X Y, et al. Generator Sources of EEG Large Waves Elicited by Mental Stress of Memory Recall or Mental Calculation[J]. The Japanese journal of physiology,2001,51(5):621-624.
[15]Lewis R S, Weekes N Y, Wang T H. The effect of a naturalistic stressor on frontal EEG asymmetry, stress, and health[J]. Biological psychology,2007,75(3):239-247.
[16]Tucker D M. Lateral brain function, emotion, and conceptualization[J]. Psychological bulletin,1981,89(1):19.
[17]Davidson R J, Schwartz G E. Saron C, et al. Frontal versus parietal EEG asymmetry during positive and negative affect[J]. Psychophysiology,1979,16(2):202-203.
[18]Davidson R J. Affective neuroscience and psychophysiology:Toward a synthesis[J]. Psychophysiology,2003,40(5):655-665.
[19]Davidson R J, Jackson D C, Kalin N H. Emotion, plasticity, context, and regulation: perspectives from affective neuroscience[J]. Psychological bulletin,2000,126(6):890.
[20]Davidson R J. Anterior cerebral asymmetry and the nature of emotion[J]. Brain and cognition,1992,20(1):125-151.
[21]Bierhaus A, Wolf J, Andrassy M, et al. A mechanism converting psychosocial stress into mononuclear cell activation[J]. Proceedings of the National Academy of Sciences,2003, 100(4):1920-1925.
[22]Epel E S, Blackburn E H, Lin J, et al. Accelerated telomere shortening in response to life stress[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004,101(49):17312-17315.
[23]Hosseini S A, Khalilzadeh M A. Emotional stress recognition system using EEG and psychophysiological signals:Using new labelling process of EEG signals in emotional stress state[C]//Biomedical Engineering and Computer Science (ICBECS),2010 International Conference on. IEEE,2010:1-6.
[24]Segerstrom S C, Miller G E. Psychological stress and the human immune system:a meta-analytic study of 30 years of inquiry[J]. Psychological bulletin,2004,130(4):601.
[25]Cohen S, Tyrrell D A J, Smith A P. Negative life events, perceived stress, negative affect, and susceptibility to the common cold[J]. Journal of personality and social psychology,1993, 64:131-131.
[26]Papousek I, Schulter G. Covariations of EEG asymmetries and emotional states indicate that activity at frontopolar locations is particularly affected by state factors[J]. Psychophysiology,2002,39(3):350-360.
[27]Hammen C. Stress and depression[J]. Annu. Rev. Clin. Psychol.,2005,1:293-319.
[28]McGonagle K A, Kessler R C. Chronic stress, acute stress, and depressive symptoms[J]. American Journal of Community Psychology,1990,18(5):681-706.
[29]Blackhart G C, Minnix J A, Kline J P. Can EEG asymmetry patterns predict future development of anxiety and depression?:A preliminary study[J]. Biological psychology, 2006,72(1):46-50.
[30]Li Y, Tong S, Liu D, et al. Abnormal EEG complexity in patients with schizophrenia and depression[J]. Clinical Neurophysiology,2008,119(6):1232-1241.
[31]Sulaiman N, Taib M N, Lias S, et al. EEG-based Stress Features Using Spectral Centroids Technique and k-Nearest Neighbor Classifier[C]//Computer Modelling and Simulation (UKSim),2011 UkSim 13th International Conference on. IEEE,2011:69-74.
[32]Fan X A, Bi L Z, Chen Z L. Using EEG to detect drivers'emotion with Bayesian Networks[C]//Machine Learning and Cybernetics (ICMLC),2010 International Conference on. IEEE.2010,3:1177-1181.
[33]Rani P, Sims J, Brackin R, et al. Online stress detection using psychophysiological signals for implicit human-robot cooperation[J], Robotica,2002,20(06):673-685.
[34]Peng H, Hu B, Qi Y, et al. An improved EEG de-noising approach in electroencephalogram (EEG) for home care[C]//Pervasive Computing Technologies for Healthcare (PervasiveHealth),2011 th International Conference on. IEEE,2011:469-474.
[35]RRNYI A. On measures of entropy and information[C]//Fourth Berkeley Symposium on Mathematical Statistics and Probability.1961:547-561.
[36]Lempel A, Ziv J. On the complexity of finite sequences[J]. Information Theory, IEEE Transactions on,1976,22(1):75-81.
[37]San-Ru H, Bo-Yu H, Xiao-Qiang X, et al. How to control a geometric quantum gatefJ]. Chinese Physics,2002,11(2):109.
[38]张佃中.非线性时间序列互信息与Lempel-Ziv复杂度的相关性研究[J].物理学报,2007，6.
[39]谢勇,徐健学,杨红军,等.皮层脑电时间序列的相空间重构及非线性特征量的提取[J].物理学报,2005,51(2)：205-214.
[40]洪时中.非线性时间序列分析的最新进展及其在地球科学中的应用前景[J].地球科学进展,1999,14(6)：559-565.
[41]Dian-Zhong Z. Research on the correlation between the mutual information and Lempel-Ziv complexity of nonlinear time series[].2007.
[42]陈芳,顾凡及,徐京华,刘增荣,刘仁.一种新的人脑信息传输复杂性的研究[J].生物物理学报,1998,14(3)：508-512
[43]Dharmawan Z. Analysis of computer games player stress level using EEG data[J]. Master of Science Thesis Report, Delft University of Technology, Netherlands,2007.
[44]Peng H, Hu B, Zheng F, et al. A method of identifying chronic stress by EEG[J]. Personal and Ubiquitous Computing,2012:1-7.
[45]Zhao W, Liu L, Zheng F, et al. Investigation into stress of mothers with mental retardation children based on EEG (electroencephalography) and psychology instruments[M]//Brain Informatics. Springer Berlin Heidelberg,2011:238-249.
[46]Pan W, Zhang L, Xia Y. The difference in EEG theta waves between concentrative and non-concentrative qigong states--a power spectrum and topographic mapping study[J]. Journal of traditional Chinese medicine= Chung i tsa chih ying wen pan/sponsored by All-China Association of Traditional Chinese Medicine, Academy of Traditional Chinese Medicine,1994,14(3):212.
[47]Bos D O. EEG-based emotion recognition[J]. The Influence of Visual and Auditory Stimuli,2006.
[48]Java RMI维基百科http://zh.wikipedia.org/wiki/Java RMI.