Physiological Signal Analysis for Cognitive State Estimation

Abstract

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.

Human emotion modeling based on salient global features of EEG signal

“…In previous work some researchers [6] have discussed the major aspects of using EEG /ERP based experiments including the recording of signals, removing noise, estimating ERP signals & signal analysis for better understanding of neural correlates of processes involved in creativity. The consequences of mental conditions due to the variation of electrocardiogram, electroencephalogram and blood pressure using discrete Fourier transform are described as in [7]. Authors as in [8] have discussed the mental behavior detection from the EEG signal and also the findings of effective data recording from physiological signals, feature extraction through wavelet transform, data reduction, feature classification using various classification methods, real time applications.…”

Cardiac Function Evaluation Analyzing Spectral Components due to the Consumption of Energy Drinks

“…ECG and pulse can be used to determine the cardiac activity or function using the parameters such as R peak amplitude, QRS complex, R-R interval, p-p amplitude of pulse, pulse rate etc. The spectral component of ECG data has been used to estimate the cognitive states (Ahmad et al, 2012). The spectral or frequency components of ECG and pulse can also be used to evaluate cardiac function.…”