多任务中枢疲劳脑电的线性描述符参数分析
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摘要
该文首先选取50名受试者分别完成3种不同类型长时间脑力认知任务,而后采用主观评价、行为学分析和事件相关电位P300对实验前后的疲劳状态进行分析,研究结果表明长时间脑力认知任务后,受试者的主观感觉疲劳程度增加,复杂运算任务的平均反应时间显著增加,转换实验任务的错误率显著增加,Fz、Cz和Pz电极位置P300的幅度均显著降低,说明受试者的大脑处理信息的能力、紧急应变能力和判断能力下降,进而验证3种类型的脑力劳动任务均不同程度地诱发了中枢疲劳程度的增加。为充分利用多导脑电信息,提出了运用线性描述符参数对实验任务前后大脑总体状态变化情况进行分析。研究结果表明,完成任务后中央和顶叶脑区能量增加,而前额、中央和顶叶脑区场强变化率下降。线性描述符参数可以从不同角度全面地描述多导脑电信号随中枢疲劳深度变化所形成的大脑整体活动状态变化的物理特性,从而更好地揭示中枢疲劳作用机制,为中枢疲劳的多通道脑电分析开辟了一个新的窗口。
In this paper, fifty subjects were selected to complete three different types of continuous long-term mental tasks, and subjective self-reporting measures, behavioral performance and P300 components of event-related potential(ERP) were used to analyze the fatigue state before and after the experiment. The results showed that after a long-term mental task, the subjective sensory fatigue increased, the average response time of the complex arithmetic task increased significantly, the error rate of the switch task increased significantly, and the amplitude of P300 at the Fz, Cz and Pz electrode positions decreased significantly, indicating that the ability of the brain's information processing, emergency response and judge decline. The results also verified that three types of mental tasks have different degrees to induce the increase of mental fatigue. In order to make full use of multi-channel electroencephalogram(EEG)'s information, the linear descriptor parameters were put forward to analyze the change of brain's overall state before and after the experimental task. The study results showed that the energy of the central and parietal brain regions increased after the task was completed, while the changes of the field strength in the forehead, central and parietal lobe decreased. The linear descriptor parameters can comprehensively describe the physical characteristics of the changes in the overall state of the brain's activity caused by the change of the mental fatigue depth from different angles, so as to better reveal the mechanism of mental fatigue. It opens a new window for multi-channel EEG's analysis of mental fatigue.
In this paper, fifty subjects were selected to complete three different types of continuous long-term mental tasks, and subjective self-reporting measures, behavioral performance and P300 components of event-related potential(ERP) were used to analyze the fatigue state before and after the experiment. The results showed that after a long-term mental task, the subjective sensory fatigue increased, the average response time of the complex arithmetic task increased significantly, the error rate of the switch task increased significantly, and the amplitude of P300 at the Fz, Cz and Pz electrode positions decreased significantly, indicating that the ability of the brain's information processing, emergency response and judge decline. The results also verified that three types of mental tasks have different degrees to induce the increase of mental fatigue. In order to make full use of multi-channel electroencephalogram(EEG)'s information, the linear descriptor parameters were put forward to analyze the change of brain's overall state before and after the experimental task. The study results showed that the energy of the central and parietal brain regions increased after the task was completed, while the changes of the field strength in the forehead, central and parietal lobe decreased. The linear descriptor parameters can comprehensively describe the physical characteristics of the changes in the overall state of the brain's activity caused by the change of the mental fatigue depth from different angles, so as to better reveal the mechanism of mental fatigue. It opens a new window for multi-channel EEG's analysis of mental fatigue.
引文
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[12]TREJO L J,KOCHAVI R,KUBITZ K,et al.Measures and models for predicting cognitive fatigue[J].Proceedings of SPIE,2005(1):105-115.
[13]LORIST M M,KLEIN M,NIEUWENHUIS S,et al.Mental fatigue and task control:Planning and preparation[J].Psychophysiology,2000,37(5):614-625.
[14]BOKSEM M A S,MEIJMAN T F,LORIST M M.Mental fatigue,motivation and action monitoring[J].Biological Psychology,2006,72(2):123-132.
[15]HODDES E,ZARCONE V,SMYTHE H,et al.Quantification of sleepiness:A new approach[J].Psychophysiology,1973,10(1):431-436.
[16]AKERSTEDT T,GILLBERG M.Subjective and objective sleepiness in the active individual[J].International Journal of Neuroscience,1990,52(1):29-37.
[17]SAMN S W,PERELLI L P.Estimating aircrew fatigue:Atechnique with implications to airlift operations[R].Texas,USA:USAF School of Aerospace Medicine,1982.
[18]BORG G.Borg’s perceived exertion and pain scales[M].Champaign,IL:Human Kinetics,1998.
[2]BOKSEM M A S,MEIJMAN T F,LORIST M M.Effects of mental fatigue on attention:An ERP study[J].Cognitive Brain Research,2005,25(1):107-116.
[3]BOKSEM M A S,KOSTERMANS E,TOPS M,et al.Individual differences in asymmetric resting-state frontal cortical activity modulate ERPs and performance in a global-local attention task[J].Journal of Psychophysiology,2012,26(2):51-62.
[4]曹雪亮,苗丹民,刘练红.脑力疲劳评定方法现状[J].第四军医大学学报,2006,27(4):382-384.CHAO Xue-liang,MIAO Dan-min,LIU Lian-hong.Current status of mental fatigue’s assessment method[J].Journal of Medical Colleges of PLA,2006,27(4):382-384.
[5]JUNG T P,MAKEIG S,STENSMO M.Estimating alertness from the EEG power spectrum[J].IEEE Transactions on Biomedical Engineering,1997,44(1):60-69.
[6]K?THNER I,WRIESSNEGGER S C,MüLLERPUTZ G R,et al.Effects of mental workload and fatigue on the P300,alpha and theta band power during operation of an ERP(P300)brain-computer interface[J].Biological Psychology,2014,102(5):118-129.
[7]MUN S C,KIM E S,PARK M C.Effect of mental fatigue caused by mobile 3D viewing on selective attention:An ERP study[J].International Journal of Psychophysiology,2014,94(1):373-381.
[8]WASCHER E,HEPPNER H,KOBALD S O,et al.Age-sensitive effects of enduring work with alternating cognitive and physical load:A study applying mobile EEGin a real life working scenario[J].Frontiers in Human Neuroscience,2016,9(711):1-14.
[9]WACKERMANN J.Beyond mapping:Estimating complexity of multichannel EEG recordings[J].Acta Neurobiologiae Experimentalis(Wars),1996,56(1):197-208.
[10]WACKERMANN J.Towards a quantitative characterization of functional states of the brain:From the non-linear methodology to the global linear description[J].International Journal of Psychophysiology,1999,34(1):65-80.
[11]LOU W,XU J,SHENG H S,et al.Multichannel linear descriptors analysis for event-related EEG of vascular dementia patients during visual detection task[J].Clinical Neurophysiology,2011,122(1):2151-2156.
[12]TREJO L J,KOCHAVI R,KUBITZ K,et al.Measures and models for predicting cognitive fatigue[J].Proceedings of SPIE,2005(1):105-115.
[13]LORIST M M,KLEIN M,NIEUWENHUIS S,et al.Mental fatigue and task control:Planning and preparation[J].Psychophysiology,2000,37(5):614-625.
[14]BOKSEM M A S,MEIJMAN T F,LORIST M M.Mental fatigue,motivation and action monitoring[J].Biological Psychology,2006,72(2):123-132.
[15]HODDES E,ZARCONE V,SMYTHE H,et al.Quantification of sleepiness:A new approach[J].Psychophysiology,1973,10(1):431-436.
[16]AKERSTEDT T,GILLBERG M.Subjective and objective sleepiness in the active individual[J].International Journal of Neuroscience,1990,52(1):29-37.
[17]SAMN S W,PERELLI L P.Estimating aircrew fatigue:Atechnique with implications to airlift operations[R].Texas,USA:USAF School of Aerospace Medicine,1982.
[18]BORG G.Borg’s perceived exertion and pain scales[M].Champaign,IL:Human Kinetics,1998.