The Relationship between Stress Levels Measured by a Questionnaire and the Data Obtained by Smart Glasses and Finger Pulse Oximeters among Polish Dental Students

Mocny‐Pachońska, Katarzyna; Doniec, Rafał; Sieciński, Szymon; Piaseczna, Natalia; Pachoński, Marek; Tkacz, Ewaryst

doi:10.3390/app11188648

Cited by 5 publications

(3 citation statements)

References 79 publications

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“…The smaller of pNN50 and Mrr indicated lower heartbeat variability, so subjects' arousal was increased, meaning that the PSNS activity decreased. These results were consistent with previous studies where HR increased during stressful tasks [73].…”

Section: Stress Recognitionsupporting

confidence: 94%

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Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

et al. 2022

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Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest.

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Section: Stress Recognitionsupporting

confidence: 94%

“…Using different sources of bio-signals to detect stress, several studies have shown that features coming from the ECG signal are significant [60], have high correlation indexes with the perceived stress level (PSS) [73], and very high accuracy rates [72].…”

Section: Stress Recognitionmentioning

confidence: 99%

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

et al. 2022

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“…These physiological changes have led to the use of various devices to detect public speaking anxiety by recording changes in heart rate ( Croft et al, 2004 ), blood oxygen saturation ( Mocny-Pachońska et al, 2021 ), skin conductance ( Kimani and Bickmore, 2019 ), or cortical activity ( Miskovic et al, 2010 ).…”

Section: Introductionmentioning

confidence: 99%

Embodied strategies for public speaking anxiety: evaluation of the Corp-Oral program

García-Monge,

Guijarro-Romero,

Santamaría-Vázquez

et al. 2023

Front. Hum. Neurosci.

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BackgroundPublic speaking is an indispensable skill that can profoundly influence success in both professional and personal spheres. Regrettably, managing anxiety during a speech poses a significant challenge for many of the population. This research assessed the impacts of a Corp-Oral program, designed to manage public speaking anxiety in university students, based on, body awareness, embodied message techniques, simulation, embodied visualization, body transformation, and gesture enhancement.MethodsThirty-six students (61% women; Mage = 20.22, SD = 1.23 years) were randomly assigned to either an experimental group (n = 18), which underwent the Corp-Oral program, or a control group (n = 18). Self-perceived anxiety, heart rate, and electroencephalography were measured in a pre-test and a post-test.ResultsThe study reveals that the Corp-Oral program significantly (p < 0.005) reduced both physiological responses (heart rate) and self-reported measures of anxiety. The alteration was more noticeable in self-reported anxiety measures (a decrease of 33.217%) than in heart rate (a decrease of 4.659%). During the speech, the experimental group exhibited increased cortical activation in areas related to emotional regulation, consciousness, sensorimotor integration, and movement control. A significant increase in frontal alpha asymmetry was observed for the experimental group in the post-test, but there were no significant variations in the theta/beta ratio.ConclusionThese findings underline the benefit of managing public speaking anxiety not merely by reducing it but by channeling it through embodied strategies. These strategies could lead to greater action awareness that would cushion the physiological effect of the anxiety response and help generate a better self-perception of the anxiety state.

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Effective affective EEG-based indicators in emotion-evoking VR environments: an evidence from machine learning

Castiblanco Jimenez,

Olivetti,

Vezzetti

et al. 2024

Neural Comput & Applic

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This study investigates the use of electroencephalography (EEG) to characterize emotions and provides insights into the consistency between self-reported and machine learning outcomes. Thirty participants engaged in five virtual reality environments designed to elicit specific emotions, while their brain activity was recorded. The participants self-assessed their ground truth emotional state in terms of Arousal and Valence through a Self-Assessment Manikin. Gradient Boosted Decision Tree was adopted as a classification algorithm to test the EEG feasibility in the characterization of emotional states. Distinctive patterns of neural activation corresponding to different levels of Valence and Arousal emerged, and a noteworthy correspondence between the outcomes of the self-assessments and the classifier suggested that EEG-based affective indicators can be successfully applied in emotional characterization, shedding light on the possibility of using them as ground truth measurements. These findings provide compelling evidence for the validity of EEG as a tool for emotion characterization and its contribution to a better understanding of emotional activation.

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The Relationship between Stress Levels Measured by a Questionnaire and the Data Obtained by Smart Glasses and Finger Pulse Oximeters among Polish Dental Students

Cited by 5 publications

References 79 publications

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

Embodied strategies for public speaking anxiety: evaluation of the Corp-Oral program

Effective affective EEG-based indicators in emotion-evoking VR environments: an evidence from machine learning

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