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Physiological signal analysis for cognitive state estimation

机译:用于认知状态估计的生理信号分析

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摘要

The purpose of this paper is to identify inconsistency in human physiological signals based on cognitive states by measuring and analyzing bio-signals. In this paper, the cognitive states are estimated using physiological signal analysis. The parameters are electrocardiogram (ECG), electromyogram (EMG), electroencephalogram (EEG) and blood pressure (BP). The signals have been collected using BIOPAC system in which the subjects were induced to undergo the specific sequence of the cognitive state. For getting physiological signals during different conditions, we utilized power point slide show, video clips and question answer method which elicits mental reactions from the subjects. Data is taken before and after four tasks that encompassed the motor action (MA), thought (TH), memory related (MR) and emotion (EM). These measured values are analyzed using BIOPAC Acknowledge software. It was found that the motor action and thought states have effects on BP while MR and EM state mainly affect the ECG measurement. The decibel value and frequency found for EM state in ECG are minimum compared to relaxed state (RS) condition. Similarly, the maximum frequency and dB value is found for MR state. No significant variation was seen for MA and TH states. Thus it was decided that the MR and EM states mainly affect the ECG measurement. For BP the value increases in MA state and decreases in TH state. The MA state mainly affects the EMG signal while other states have no significant changes. The EEG mainly detects the signal of task performed by the specific brain region where the electrodes are placed. In EEG analysis, the electrodes are placed in occipital lobe region which gives mainly the variation in alpha amplitude of EEG with eyes closed and eyes opened. Alpha wave amplitudes vary with the subjects attention to mental tasks performed with eyes closed.
机译:本文的目的是通过测量和分析生物信号来基于认知状态识别人体生理信号中的不一致。在本文中,使用生理信号分析来估计认知状态。参数是心电图(ECG),肌电图(EMG),脑电图(EEG)和血压(BP)。信号是使用BIOPAC系统收集的,在该系统中,受试者被诱导经历了特定的认知状态序列。为了获得不同条件下的生理信号,我们利用了幻灯片演示,视频剪辑和问题解答方法,这些方法引起了受试者的心理反应。在四个任务之前和之后获取数据,这些任务包括运动动作(MA),思维(TH),与记忆有关(MR)和情绪(EM)。使用BIOPAC Acknowledge软件分析这些测量值。发现运动行为和思想状态对血压有影响,而MR和EM状态主要影响心电图测量。与放松状态(RS)条件相比,在ECG中为EM状态找到的分贝值和频率最小。类似地,找到MR状态的最大频率和dB值。对于MA和TH状态,未见明显变化。因此,可以确定MR和EM状态主要影响ECG测量。对于BP,值在MA状态下增加,而在TH状态下减小。 MA状态主要影响EMG信号,而其他状态没有明显变化。脑电图主要检测由放置电极的特定大脑区域执行的任务信号。在脑电图分析中,将电极放置在枕叶区域,这在闭眼和睁眼时主要给出脑电图的α振幅变化。阿尔法波幅度随受试者对闭眼执行的心理任务的注意而变化。

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