Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Onita, C. A.; Matei, D. -V.; Chelarasu, E.; Lupu, R. G.; Petrescu-Miron, D.; Visnevschi, A.; Vudu, S.; Corciova, C.; Fuior, R.; Tupita, N.; Bouchard, S.; Mocanu, V.
Virtual Reality Trier Social Stress and Virtual Supermarket Exposure: Electrocardiogram Correlates of Food Craving and Eating Traits in Adolescents Article de journal
Dans: Nutrients, vol. 17, no 24, 2025, ISSN: 20726643 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: acute stress, Adolescent, Adolescents, adult, article, controlled study, craving, decision making, Eating, eating behavior, ecological validity, electrocardiogram, electrocardiogram (ECG) parameters, Electrocardiography, feeding behavior, female, food craving, food preference, Food Preferences, Heart Rate, human, Humans, hyperphagia, male, mental stress, motivation, normal human, overnutrition, pathophysiology, Perceived Stress Scale, personalized nutrition, physiological stress, physiology, PQ interval, Psychological, psychology, QTc interval, questionnaire, reward, simulation, social stress, Stress, supermarket, Surveys and Questionnaires, three-factor eating questionnaire (TFEQ), Three-Factor-Eating-Questionnaire, Trier Social Stress Test, virtual reality, virtual supermarket, visual analog scale
@article{onita_virtual_2025,
title = {Virtual Reality Trier Social Stress and Virtual Supermarket Exposure: Electrocardiogram Correlates of Food Craving and Eating Traits in Adolescents},
author = {C. A. Onita and D. -V. Matei and E. Chelarasu and R. G. Lupu and D. Petrescu-Miron and A. Visnevschi and S. Vudu and C. Corciova and R. Fuior and N. Tupita and S. Bouchard and V. Mocanu},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105026068857&doi=10.3390%2Fnu17243924&partnerID=40&md5=fde16e892b1a18284dc51ac869ba8ee9},
doi = {10.3390/nu17243924},
issn = {20726643 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Nutrients},
volume = {17},
number = {24},
abstract = {Background/Objectives: Acute stress is known to influence food-related motivation and decision-making, often promoting a preference for energy-dense, palatable foods. However, traditional laboratory paradigms have limited ecological validity. This study examined the relationship between stress-induced physiological changes, eating behavior traits, and food cravings using a virtual reality (VR) adaptation of the Trier Social Stress Test (VR-TSST) followed by a VR supermarket task in adolescents. Methods: Thirty-eight adolescents (mean age 15.8 ± 0.6 years) participated in the study. Physiological parameters (HR, QT, PQ intervals) were recorded pre- and post-stress using a portable ECG device (WIWE). Perceived stress and eating behavior traits were evaluated with the Perceived Stress Scale (PSS) and the Three-Factor Eating Questionnaire (TFEQ-R21C), respectively. Immediately after the VR-TSST, participants performed a VR supermarket task in which they rated cravings for sweet, fatty, and healthy foods using visual analog scales (VAS). Paired-samples t-tests examined pre–post changes in physiological parameters, partial correlations explored associations between ECG responses and eating traits, and a 2 × 3 mixed-model Repeated Measures ANOVA assessed the effects of food type (sweet, fatty, healthy) and uncontrolled eating (UE) group (low vs. high) on post-stress cravings. Results: Acute stress induced significant increases in HR and QTc intervals (p < 0.01), confirming a robust physiological stress response. The ANOVA revealed a strong main effect of food type (F(1.93, 435.41) = 168.98, p < 0.001, η2p = 0.43), indicating that stress-induced cravings differed across food categories, with sweet foods rated highest. A significant food type × UE group interaction (F(1.93, 435.41) = 16.49, p < 0.001, η2p = 0.07) showed that adolescents with high UE exhibited greater cravings for sweet and fatty foods than those with low UE. Overall, craving levels did not differ significantly between groups. Conclusions: The findings demonstrate that acute stress selectively enhances cravings for high-reward foods, and that this effect is modulated by baseline uncontrolled eating tendencies. The combined use of VR-based stress induction and VR supermarket simulation offers an innovative, ecologically valid framework for studying stress-related eating behavior in adolescents, with potential implications for personalized nutrition and the prevention of stress-induced overeating. © 2025 by the authors.},
keywords = {acute stress, Adolescent, Adolescents, adult, article, controlled study, craving, decision making, Eating, eating behavior, ecological validity, electrocardiogram, electrocardiogram (ECG) parameters, Electrocardiography, feeding behavior, female, food craving, food preference, Food Preferences, Heart Rate, human, Humans, hyperphagia, male, mental stress, motivation, normal human, overnutrition, pathophysiology, Perceived Stress Scale, personalized nutrition, physiological stress, physiology, PQ interval, Psychological, psychology, QTc interval, questionnaire, reward, simulation, social stress, Stress, supermarket, Surveys and Questionnaires, three-factor eating questionnaire (TFEQ), Three-Factor-Eating-Questionnaire, Trier Social Stress Test, virtual reality, virtual supermarket, visual analog scale},
pubstate = {published},
tppubtype = {article}
}
Background/Objectives: Acute stress is known to influence food-related motivation and decision-making, often promoting a preference for energy-dense, palatable foods. However, traditional laboratory paradigms have limited ecological validity. This study examined the relationship between stress-induced physiological changes, eating behavior traits, and food cravings using a virtual reality (VR) adaptation of the Trier Social Stress Test (VR-TSST) followed by a VR supermarket task in adolescents. Methods: Thirty-eight adolescents (mean age 15.8 ± 0.6 years) participated in the study. Physiological parameters (HR, QT, PQ intervals) were recorded pre- and post-stress using a portable ECG device (WIWE). Perceived stress and eating behavior traits were evaluated with the Perceived Stress Scale (PSS) and the Three-Factor Eating Questionnaire (TFEQ-R21C), respectively. Immediately after the VR-TSST, participants performed a VR supermarket task in which they rated cravings for sweet, fatty, and healthy foods using visual analog scales (VAS). Paired-samples t-tests examined pre–post changes in physiological parameters, partial correlations explored associations between ECG responses and eating traits, and a 2 × 3 mixed-model Repeated Measures ANOVA assessed the effects of food type (sweet, fatty, healthy) and uncontrolled eating (UE) group (low vs. high) on post-stress cravings. Results: Acute stress induced significant increases in HR and QTc intervals (p < 0.01), confirming a robust physiological stress response. The ANOVA revealed a strong main effect of food type (F(1.93, 435.41) = 168.98, p < 0.001, η2p = 0.43), indicating that stress-induced cravings differed across food categories, with sweet foods rated highest. A significant food type × UE group interaction (F(1.93, 435.41) = 16.49, p < 0.001, η2p = 0.07) showed that adolescents with high UE exhibited greater cravings for sweet and fatty foods than those with low UE. Overall, craving levels did not differ significantly between groups. Conclusions: The findings demonstrate that acute stress selectively enhances cravings for high-reward foods, and that this effect is modulated by baseline uncontrolled eating tendencies. The combined use of VR-based stress induction and VR supermarket simulation offers an innovative, ecologically valid framework for studying stress-related eating behavior in adolescents, with potential implications for personalized nutrition and the prevention of stress-induced overeating. © 2025 by the authors.
2.
Pétrin, R.; Bérubé, A.; St-Pierre, É.; Blais, C.
Maternal childhood emotional abuse increases cardiovascular responses to children’s emotional facial expressions Article de journal
Dans: PLoS ONE, vol. 19, no 5 May, 2024, ISSN: 19326203 (ISSN), (Publisher: Public Library of Science).
Résumé | Liens | BibTeX | Étiquettes: adult, alcohol consumption, analysis of variance, article, blood pressure, cardiovascular response, Child, Child Abuse, Childhood, Childhood Trauma Questionnaire, demographics, electrocardiogram, Electrocardiography, emotion, Emotional Abuse, Emotions, Ethnicity, Facial Expression, female, Heart Rate, heart rate variability, human, human experiment, Humans, Likert scale, male, mother, mother child relation, Mother-Child Relations, Mothers, parasympathetic tone, physical activity, physiology, post hoc analysis, psychology, questionnaire, sexual abuse, Surveys and Questionnaires
@article{petrin_maternal_2024,
title = {Maternal childhood emotional abuse increases cardiovascular responses to children’s emotional facial expressions},
author = {R. Pétrin and A. Bérubé and É. St-Pierre and C. Blais},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192637581&doi=10.1371%2fjournal.pone.0302782&partnerID=40&md5=c464b30fe7cc5b7b0baaf865fdf1f6de},
doi = {10.1371/journal.pone.0302782},
issn = {19326203 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {PLoS ONE},
volume = {19},
number = {5 May},
publisher = {Public Library of Science},
abstract = {Parents with a history of childhood maltreatment may be more likely to respond inadequately to their child’s emotional cues, such as crying or screaming, due to previous exposure to prolonged stress. While studies have investigated parents’ physiological reactions to their children’s vocal expressions of emotions, less attention has been given to their responses when perceiving children’s facial expressions of emotions. The present study aimed to determine if viewing facial expressions of emotions in children induces cardiovascular changes in mothers (hypo- or hyper-arousal) and whether these differ as a function of childhood maltreatment. A total of 104 mothers took part in this study. Their experiences of childhood maltreatment were measured using the Childhood Trauma Questionnaire (CTQ). Participants’ electrocardiogram signals were recorded during a task in which they viewed a landscape video (baseline) and images of children’s faces expressing different intensities of emotion. Heart rate variability (HRV) was extracted from the recordings as an indicator of parasympathetic reactivity. Participants presented two profiles: one group of mothers had a decreased HRV when presented with images of children’s facial expressions of emotions, while the other group’s HRV increased. However, HRV change was not significantly different between the two groups. The interaction between HRV groups and the severity of maltreatment experienced was marginal. Results suggested that experiences of childhood emotional abuse were more common in mothers whose HRV increased during the task. Therefore, more severe childhood experiences of emotional abuse could be associated with mothers’ cardiovascular hyperreactivity. Maladaptive cardiovascular responses could have a ripple effect, influencing how mothers react to their children’s facial expressions of emotions. That reaction could affect the quality of their interaction with their child. Providing interventions that help parents regulate their physiological and behavioral responses to stress might be helpful, especially if they have experienced childhood maltreatment. © 2024 Public Library of Science. All rights reserved.},
note = {Publisher: Public Library of Science},
keywords = {adult, alcohol consumption, analysis of variance, article, blood pressure, cardiovascular response, Child, Child Abuse, Childhood, Childhood Trauma Questionnaire, demographics, electrocardiogram, Electrocardiography, emotion, Emotional Abuse, Emotions, Ethnicity, Facial Expression, female, Heart Rate, heart rate variability, human, human experiment, Humans, Likert scale, male, mother, mother child relation, Mother-Child Relations, Mothers, parasympathetic tone, physical activity, physiology, post hoc analysis, psychology, questionnaire, sexual abuse, Surveys and Questionnaires},
pubstate = {published},
tppubtype = {article}
}
Parents with a history of childhood maltreatment may be more likely to respond inadequately to their child’s emotional cues, such as crying or screaming, due to previous exposure to prolonged stress. While studies have investigated parents’ physiological reactions to their children’s vocal expressions of emotions, less attention has been given to their responses when perceiving children’s facial expressions of emotions. The present study aimed to determine if viewing facial expressions of emotions in children induces cardiovascular changes in mothers (hypo- or hyper-arousal) and whether these differ as a function of childhood maltreatment. A total of 104 mothers took part in this study. Their experiences of childhood maltreatment were measured using the Childhood Trauma Questionnaire (CTQ). Participants’ electrocardiogram signals were recorded during a task in which they viewed a landscape video (baseline) and images of children’s faces expressing different intensities of emotion. Heart rate variability (HRV) was extracted from the recordings as an indicator of parasympathetic reactivity. Participants presented two profiles: one group of mothers had a decreased HRV when presented with images of children’s facial expressions of emotions, while the other group’s HRV increased. However, HRV change was not significantly different between the two groups. The interaction between HRV groups and the severity of maltreatment experienced was marginal. Results suggested that experiences of childhood emotional abuse were more common in mothers whose HRV increased during the task. Therefore, more severe childhood experiences of emotional abuse could be associated with mothers’ cardiovascular hyperreactivity. Maladaptive cardiovascular responses could have a ripple effect, influencing how mothers react to their children’s facial expressions of emotions. That reaction could affect the quality of their interaction with their child. Providing interventions that help parents regulate their physiological and behavioral responses to stress might be helpful, especially if they have experienced childhood maltreatment. © 2024 Public Library of Science. All rights reserved.
3.
Joudeh, I. O.; Cretu, A. -M.; Bouchard, S.; Guimond, S.
Prediction of Continuous Emotional Measures through Physiological and Visual Data † Article de journal
Dans: Sensors, vol. 23, no 12, p. 17–21, 2023, ISSN: 14248220, (Publisher: Interactive Media Institute).
Résumé | Liens | BibTeX | Étiquettes: Affect recognition, Affective state, Arousal, Data-source, Deep learning, Electrocardiography, emotion, Emotion Recognition, Emotions, face recognition, Faces detection, Forecasting, human, Humans, Images processing, Learning systems, Machine learning, Machine-learning, mental disease, Mental Disorders, Physiological data, physiology, Signal-processing, Statistical tests, Video recording, Virtual-reality environment
@article{joudeh_prediction_2023-1,
title = {Prediction of Continuous Emotional Measures through Physiological and Visual Data †},
author = {I. O. Joudeh and A. -M. Cretu and S. Bouchard and S. Guimond},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163943735&doi=10.3390%2fs23125613&partnerID=40&md5=5e970f0d8c5790b85d8d77a9f3f52a2d},
doi = {10.3390/s23125613},
issn = {14248220},
year = {2023},
date = {2023-01-01},
journal = {Sensors},
volume = {23},
number = {12},
pages = {17–21},
publisher = {MDPI},
abstract = {The affective state of a person can be measured using arousal and valence values. In this article, we contribute to the prediction of arousal and valence values from various data sources. Our goal is to later use such predictive models to adaptively adjust virtual reality (VR) environments and help facilitate cognitive remediation exercises for users with mental health disorders, such as schizophrenia, while avoiding discouragement. Building on our previous work on physiological, electrodermal activity (EDA) and electrocardiogram (ECG) recordings, we propose improving preprocessing and adding novel feature selection and decision fusion processes. We use video recordings as an additional data source for predicting affective states. We implement an innovative solution based on a combination of machine learning models alongside a series of preprocessing steps. We test our approach on RECOLA, a publicly available dataset. The best results are obtained with a concordance correlation coefficient (CCC) of 0.996 for arousal and 0.998 for valence using physiological data. Related work in the literature reported lower CCCs on the same data modality; thus, our approach outperforms the state-of-the-art approaches for RECOLA. Our study underscores the potential of using advanced machine learning techniques with diverse data sources to enhance the personalization of VR environments. © 2023 by the authors.},
note = {Publisher: Interactive Media Institute},
keywords = {Affect recognition, Affective state, Arousal, Data-source, Deep learning, Electrocardiography, emotion, Emotion Recognition, Emotions, face recognition, Faces detection, Forecasting, human, Humans, Images processing, Learning systems, Machine learning, Machine-learning, mental disease, Mental Disorders, Physiological data, physiology, Signal-processing, Statistical tests, Video recording, Virtual-reality environment},
pubstate = {published},
tppubtype = {article}
}
The affective state of a person can be measured using arousal and valence values. In this article, we contribute to the prediction of arousal and valence values from various data sources. Our goal is to later use such predictive models to adaptively adjust virtual reality (VR) environments and help facilitate cognitive remediation exercises for users with mental health disorders, such as schizophrenia, while avoiding discouragement. Building on our previous work on physiological, electrodermal activity (EDA) and electrocardiogram (ECG) recordings, we propose improving preprocessing and adding novel feature selection and decision fusion processes. We use video recordings as an additional data source for predicting affective states. We implement an innovative solution based on a combination of machine learning models alongside a series of preprocessing steps. We test our approach on RECOLA, a publicly available dataset. The best results are obtained with a concordance correlation coefficient (CCC) of 0.996 for arousal and 0.998 for valence using physiological data. Related work in the literature reported lower CCCs on the same data modality; thus, our approach outperforms the state-of-the-art approaches for RECOLA. Our study underscores the potential of using advanced machine learning techniques with diverse data sources to enhance the personalization of VR environments. © 2023 by the authors.