scholarly journals Classification of Mental Stress Levels by Analyzing fNIRS Signal Using Linear and Non-linear Features

2018 ◽  
Vol 5 (2) ◽  
pp. 55-61 ◽  
Author(s):  
Reza Arefi Shirvan ◽  
Seyed Kamaledin Setarehdan ◽  
Ali Motie Nasrabadi
Keyword(s):  
Prefrontal Cortex ◽  
Mental Stress ◽  
Near Infrared ◽  
Mental Arithmetic ◽  
Influential Factors ◽  
Functional Near Infrared Spectroscopy ◽  
Arithmetic Task ◽  
Stress Levels ◽  
Nonlinear Features ◽  
Linear And Nonlinear

Background: Mental stress is known as one of the main influential factors in development of different diseases including heart attack and stroke. Thus, quantification of stress level can be very important in preventing many diseases and in human health. Methods: The prefrontal cortex is involved in body regulation in response to stress. In this research, functional near infrared spectroscopy (fNIRS) signals were recorded from FP2 position in the international electroencephalographic 10–20 system during a stressful mental arithmetic task to be calculated within a limited period of time. After extracting the brain’s hemodynamic response from fNIRS signal, different linear and nonlinear features were extracted from the signal which are then used for stress levels classification both individually and in combination. Results: In this study, the maximum accuracy of 88.72% was achieved in classification between high and low stress levels, and 96.92% was obtained for the stress and rest states. Conclusion: Our results showed that using the proposed linear and nonlinear features it is possible to effectively classify stress levels from fNIRS signals recorded from only one site in the prefrontal cortex. Comparing to other methods, it is shown that the proposed algorithm outperforms other previously reported methods using the nonlinear features extracted from the fNIRS signal. These results clearly show the potential of fNIRS signal as a useful tool for early diagnosis and quantify stress.

scholarly journals Decision Fusion of EEG and fNIRS Signals

2019 ◽  
Author(s):  
Fares Al-Shargie
Keyword(s):  
Mental Stress ◽  
Near Infrared ◽  
Time Pressure ◽  
Functional Neuroimaging ◽  
Mental Arithmetic ◽  
Decision Fusion ◽  
Support Vector ◽  
Functional Near Infrared Spectroscopy ◽  
Arithmetic Task ◽  
Mental Arithmetic Task

In this study, we investigated the use of multimodal functional neuroimaging in detecting mental stress on the prefrontal cortex (PFC). We recorded Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS) simultaneously from 20-subjects performing mental arithmetic task under control and stress conditions. Stress was induced in this study based on two established stressors – time pressure and negative feedback about peer performance. We explored decision fusion by using support vector machine classifier for each modality, and optimizing the classifiers based on Receiver Operating Characteristic (ROC) curve values. Experiment results revealed significant reduction in alpha rhythm and mean change in concentration of oxygenated hemoglobin at PFC when stressed, p<0.001 and 0.0001 respectively. The decision fusion improved significantly the detection rate of mental stress by +7.76% and +10.57%, when compared to sole modality of EEG and fNIRS, respectively.

scholarly journals Athlete-Specific Neural Strategies under Pressure: A fNIRS Pilot Study

2020 ◽  
Vol 17 (22) ◽  
pp. 8464
Author(s):  
Inchon Park ◽  
Youngsook Kim ◽  
Seung Kyum Kim
Keyword(s):  
Prefrontal Cortex ◽  
Pilot Study ◽  
Near Infrared ◽  
Hemodynamic Response ◽  
Visual Simulation ◽  
Hemodynamic Responses ◽  
Functional Near Infrared Spectroscopy ◽  
Response Level ◽  
Stress Levels ◽  
Simulation Task

(1) Background: Stress and pressure during competition and training impair athletes’ performance in sports. However, the influence of mental stress on the prefrontal cortex (PFC) functioning in an athlete during the visual simulation task is unknown. The purpose of this pilot study was to investigate hemodynamic responses during the visual-simulation task that induces pressure and stress using functional near-infrared spectroscopy. (2) Methods: Ten archers and ten non-athlete collegiate students performed a visual-simulation task. Participants’ current stress levels were collected using a visual analog scale before and after the task. Average oxygenated hemoglobin (HbO), deoxygenated hemoglobin (HbR), and total hemoglobin (HbT) levels and their variability (standard deviation (SD) HbO, SD HbR, and SD HbT) were computed to compare the neural efficiency between athlete and non-athlete. (3) Results: In general, both groups exhibited increased stress levels after the simulation task, and there was no group difference in overall average hemodynamic response from PFC and dorsolateral prefrontal cortex (DLPFC). While the average hemodynamic response level did not differ between groups, variability in hemodynamic responses from the archer group showed a more stable pattern than the non-athlete group. (4) Conclusion: Under this experimental setting, decreasing the variability in hemodynamic responses during the visual simulation, potentially via stabilizing the fluctuation of PFC, was characterized by the stress-related compensatory neural strategy of elite archers.

scholarly journals Quantification of Mental Stress using fNIRS Signals

2019 ◽  
Author(s):  
Fares Al-Shargie
Keyword(s):  
Mental Stress ◽  
Task Difficulty ◽  
Near Infrared ◽  
Time Pressure ◽  
Human Subjects ◽  
Difficulty Level ◽  
Functional Near Infrared Spectroscopy ◽  
Arithmetic Task ◽  
Stress Task ◽  
Different Levels

In this study, we propose functional near infrared spectroscopy (fNIRS) to objectively grade different levels of mental stress. The levels of stress were set based on arithmetic task difficulty, time pressure and negative feedback about peer performance. We examined the proposed approach on twelve human subjects using the Montreal Imaging Stress Task. The experiment results revealed a reduction in cortical activations at prefrontal cortex when stressed, and the differences in hemodynamic response between control condition and under stress were significant with mean p-values of 0.0023, 0.00015 and 0.0004 for arithmetic difficulty level one, two and three, respectively. We thus confirm the feasibility of fNIRS in grading mental stress.

scholarly journals Fusion of fNIRS and EEG Signals: Mental Stress Study

2019 ◽  
Author(s):  
Fares Al-Shargie
Keyword(s):  
Mental Stress ◽  
Detection Rate ◽  
Near Infrared ◽  
Time Pressure ◽  
Individual Performance ◽  
Support Vector ◽  
Eeg Signals ◽  
Functional Near Infrared Spectroscopy ◽  
Arithmetic Task ◽  
Novel Approach

Fusion of Functional Near infrared Spectroscopy (fNIRS) and Electroencephalograph (EEG) is a novel approach. This study aims in improving the detection rate of mental stress using the complementary nature of fNIRS and EEG neuroimaging modality. Simultaneous measurements of fNIRS and EEG signals were conducted on 12 subjects while solving arithmetic problems under two different conditions (control and stress). The stress in this work was based on arithmetic task difficulty, time pressure and negative feedback of individual performance. The study demonstrated significant reduction in the concentration of oxygenated hemoglobin (p=0.0032) and alpha rhythm power (p=0.0213) on the PFC under stress condition. Specifically, the right PFC and dorsolateral PFC were highly sensitive to mental stress. Using support vector machine (SVM), the mean detection rate of mental stress was calculated as 91%, 95% and 98% using fNIRS, EEG and fusion of fNIRS and EEG signals respectively.

scholarly journals Rightward Shift of Two-Channel NIRS-Defined Prefrontal Cortex Activity during Mental Arithmetic Tasks with Increasing Levels of State Anxiety

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 538
Author(s):  
Miwa Horiuchi-Hirose ◽  
Kazuhiko Sawada
Keyword(s):  
Prefrontal Cortex ◽  
Task Performance ◽  
State Anxiety ◽  
Near Infrared ◽  
Mental Arithmetic ◽  
The State ◽  
High State ◽  
Experimental Task ◽  
Arithmetic Task ◽  
Anxiety Group

This study was aimed at clarifying the effect of different levels of state anxiety caused by mental arithmetic tasks on the anxiety- and/or task performance-related activation of the frontopolar prefrontal cortex (PFC). Twenty-six healthy male subjects performed two sets of mental arithmetic tasks, which consisted of two difficulty levels. Anxiety levels were evaluated subjectively by the State–Trait Anxiety Inventory-Form JYZ (STAI). Near-infrared spectroscopy (NIRS) measurements revealed greater levels of oxyhemoglobin in the frontopolar PFC during experimental tasks. When the subjects were divided into three anxiety groups based on STAI scores, arithmetic task performance was reduced in the moderate and high state anxiety groups compared the low state anxiety group during the experimental task, but not in the control task. Increased frontopolar PFC activity during the experimental task was observed on either side in the moderate anxiety group. The laterality of frontopolar PFC activity in moderate and high state anxiety groups shifted from left to right dominance, independent of task difficulty. Our findings suggested that reduced task performance increased the difficulty of the arithmetic tasks and was involved in the state anxiety-associated rightward lateralization of the frontopolar PFC.

Making social neuroscience less WEIRD: Using fNIRS to measure neural signatures of persuasive influence in a Middle East participant sample

2019 ◽  
Author(s):  
Shannon Burns ◽  
Lianne N. Barnes ◽  
Ian A. McCulloh ◽  
Munqith M. Dagher ◽  
Emily B. Falk ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Near Infrared ◽  
Brain Activity ◽  
Health And Safety ◽  
Social Neuroscience ◽  
Functional Near Infrared Spectroscopy ◽  
Future Directions ◽  
Neuroscience Research ◽  
Neuropsychological Functions ◽  
Arabic Speaking

The large majority of social neuroscience research uses WEIRD populations – participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sample. Participants were shown persuasive videos on various health and safety topics while their brain activity was measured using functional near infrared spectroscopy (fNIRS). Self-reported persuasiveness ratings for each video were then recorded. Consistent with previous research conducted with American subjects, this work found that activity in the dorsomedial and ventromedial prefrontal cortex predicted how persuasive participants found the videos and how much they intended to engage in the messages’ endorsed behaviors. Further, activity in the left ventrolateral prefrontal cortex was associated with persuasiveness ratings, but only in participants for whom the message was personally relevant. Implications for these results on the understanding of the brain basis of persuasion and on future directions for neuroimaging in diverse populations are discussed.

scholarly journals Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

2021 ◽  
Vol 11 (6) ◽  
pp. 701
Author(s):  
Cheng-Hsuan Chen ◽  
Kuo-Kai Shyu ◽  
Cheng-Kai Lu ◽  
Chi-Wen Jao ◽  
Po-Lei Lee
Keyword(s):  
Prefrontal Cortex ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Kernel Functions ◽  
Olfactory Stimulation ◽  
Support Vector ◽  
Hemodynamic Response Function ◽  
Functional Near Infrared Spectroscopy ◽  
Data Set

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

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