Effect of Daily Stress on Heart-Rate Variability during Stroop Color Word Task

Park, Soyeon; Yu, Juwon; Sun-Hwa, Kang，; Lee, Hyeonju; Dong, Suh-Yeon

doi:10.1109/embc44109.2020.9176448

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…The effects of daily stress have not yet been investigated extensively. Our previous study examined the effect of daily stress on heart rate variability (HRV) and found significant differences in values and trends for specific HRV parameters during Stroop tasks between high-and low-daily-stressful days [47]. Similar to these results, the new findings in this study are that the daily stress levels also differ in prefrontal oxygenation measured by fNIRS, and that the fNIRS signal features can be used to classify daily stress levels with stable performance.…”

Section: Discussionsupporting

confidence: 80%

Effects of Daily Stress in Mental State Classification

Park

Dong

2020

IEEE Access

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An external stimulus, event, or environment that stresses an individual is called a stressor. Many mental stress detection studies have been focused on the discrimination of the mental state with and without the experimental stressor. However, the mental state in the absence of experimental stressors may not represent accurately the nonstress (baseline) state because people inherently experience considerable stress in their daily lives. Therefore, we assumed that stress detection could be improved more accurately by considering the daily stress. In this study, functional near-infrared spectroscopy (fNIRS) was measured in 41 healthy participants to quantify their prefrontal cortical oxygenation during performing a cognitive task as an experimental stressor, considering individual daily stress level based on the self-report. We then extracted six signal features, including the slope, mean, standard deviation, peak, skewness, and kurtosis of the oxygenated hemoglobin concentration. Using various feature combinations and time windows, we successfully managed to classify daily stress (high/low) and the mental state (task/rest) with support vector machine classifiers. Specifically, individual daily stress level can be easily discriminated with signal features from fNIRS. Moreover, mental state classification performance improved significantly when the daily stress level was handled separately. The findings of this study show the feasibility of the fNIRS-based daily stress classification and can be used in the future to design a robust mental stress management system for the assessment of daily stress in individuals.INDEX TERMS daily stress, functional near-infrared spectroscopy, stroop word color task, mental stress classification.

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Section: Discussionsupporting

confidence: 80%

Effects of Daily Stress in Mental State Classification

Park

Dong

2020

IEEE Access

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“…A sensor-based quantitative assessment of heart rate variability has often been linked to cognitive performance, particularly in tasks like the Stroop task (e.g., in athletes [ 26 ], individuals with post-traumatic stress syndrome [ 27 ], and healthy subjects managing daily stress [ 28 ]), as well as to motor control (including measures such as range of motion and interoceptive accuracy [ 29 ]). However, a protocol considering these three domains together was still lacking.…”

Section: Discussionmentioning

confidence: 99%

Embodimetrics: A Principal Component Analysis Study of the Combined Assessment of Cardiac, Cognitive and Mobility Parameters

Chellini,

Salmaso,

Di Domenico

et al. 2024

Sensors

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There is a growing body of literature investigating the relationship between the frequency domain analysis of heart rate variability (HRV) and cognitive Stroop task performance. We proposed a combined assessment integrating trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac, and motor variables using principal component analysis (PCA). Additionally, we assessed changes in the relationships among these variables after a two-month intervention aimed at improving the perception–action link. At baseline, PCA correctly identified three components: one related to cardiac variables, one to trunk motion, and one to Stroop task performance. After the intervention, only two components were found, with trunk symmetry and range of motion, accuracy, time to complete the Stroop task, and low-frequency heart rate variability aggregated into a single component using PCA. Artificial neural network analysis confirmed the effects of both HRV and motor behavior on cognitive Stroop task performance. This analysis suggested that this protocol was effective in investigating embodied cognition, and we defined this approach as “embodimetrics”.

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“…Mobile ECG for calculating heart rate variability is used to evaluate the effects of different types of stress on the autonomic nervous system [32]. Heart rate variability can be used to evaluate an individual's stress response during a cognitive task [33]. Enhanced sympathetic nerve activity due to a decrease in parasympathetic nerve activity is common in acute, sub-acute, and chronic fatigue [34].…”

Section: Discussionmentioning

confidence: 99%

Executability and repeatability of a study setup using wearable and computerized technology to examine a wide range of physiological and cognitive functions of a patient outside hospital

Müller

Rautalin

Arola

et al. 2023

Preprint

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Objectives: Reasons for daily problems of a patient are often unclear as they are not systematically monitored in daily life. To remedy this, we designed a study protocol combining outpatient laboratory and home measurements. Feasibility of the protocol was evaluated by examining its executability and repeatability. Participants: Sixteen patients undergoing neurosurgery for unruptured intracranial aneurysm (UIA), each acting as their own control. Study Protocol: Two laboratory examinations followed by home recordings at 2 weeks pre- and 4-6 weeks postoperatively. In between a sole home recording at 3 weeks and 3 months postoperatively. Subjective health and performance data were gathered via an internet portal. Methods: Laboratory Day included computer-based cognitive tests on attention, working memory and executive functions. Electroencephalography (EEG), electrocardiography (ECG) and electrodermal activity (EDA) were recorded during the tests. A saccade test with electro-oculography (EOG) and event-related potentials (ERP) to emotionally loaded sounds were also done. First three home recordings included tablet-based cognitive tests, sleep polysomnography (PSG), ECG, and actigraphy; the 4th only an actigraphy and sleep diary. Outcome measures: Executability and repeatability of the protocol: Number of patients completing the study, success rate of carrying it out as planned, obtained data and patient feedback. Results: In 13 (81%) patients all data from home recordings was obtained as planned. In 11 (68%) patients the whole protocol was carried out as planned and in 3 partly. The time schedules required adjusting. Patients reported no discomfort from using wearable devices. Patients considered answering the internet-based health questionnaires cumbersome: all data was obtained only in 30%. Conclusions: Mobile technologies are a tool kit from which to choose a clinically relevant combination to obtain objective data on physical, physiologic, and cognitive performance of a patient outside hospital.

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Effect of Daily Stress on Heart-Rate Variability during Stroop Color Word Task

Cited by 3 publications

References 14 publications

Effects of Daily Stress in Mental State Classification

Effects of Daily Stress in Mental State Classification

Embodimetrics: A Principal Component Analysis Study of the Combined Assessment of Cardiac, Cognitive and Mobility Parameters

Executability and repeatability of a study setup using wearable and computerized technology to examine a wide range of physiological and cognitive functions of a patient outside hospital

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