Stress is a psycho-physiological state of the human body associated with great discomfort and distress that can dramatically affect one's emotions, physical and mental health. Such a condition can be caused by the environment (e.g. work-place) and external factors (e.g. excessive workload, illness or injury, personal problems), but also by internal factors (e.g., negative emotions, negative thoughts, insecurities, etc.). Stress has become the illness of present times affecting people regardless the gender, age, or social status, and causing a reduction in the quality of life interfering with work performance and social life. Indeed, it is associated with a range of pathological conditions (e.g. cognitive, neurovascular, cardiovascular) that can arise when stress becomes a chronic state. Therefore, methodologies to reliably assess mental stress and the underlying emotional states are required to detect harmful conditions and reduce negative effects.
Neuroimaging techniques (e.g. EEG, fNIRS, MEG) and autonomic nervous system monitoring approaches (e.g. heart rate variability, breathing rate, skin conductance) have been exploited for stress detection. Multimodal approaches, which can provide a more comprehensive understanding of the interplay between central and autonomic nervous systems in this context are therefore relevant. Moreover, advances towards a reliable assessment of the mental state are essential to allow the development of paradigms aimed at facilitating positive mental state, improve subjects’ performances and prevent stressful conditions in several environments and contexts (e.g. work-place, school, neurorehabilitation). Therefore, the goal of this research topic is to investigate, in the field of cognitive neuroergonomics, the influence of internal and external factors on mental state, detect stressful conditions and propose paradigms to prevent negative psycho-physiological effects.
This research topic will consider research papers, theories, models, and applications that present neurophysiological measures to identify and monitor the subject’s mental state in relation to potentially stressful situation. We are interested in both research that seeks to improve our understanding of the underlying neurocognitive mechanisms in response to such conditions, and papers proposing new methodology to identify and prevent stressful situations. Thus, we welcome multidisciplinary studies that address but are not limited to the following themes:
• Neurophysiological monitoring
• Influence of external factors on the neurophysiological status
• Central nervous system monitoring via unimodal or multimodal neuroimaging, optical, or electrophysiological techniques
• Autonomic nervous system monitoring (e.g. heart rate variability, breathing rate, skin conductance)
• Real-world applications
• Multi-source data integration
• Monitoring with wearable and contactless devices
• Affective computing
Stress is a psycho-physiological state of the human body associated with great discomfort and distress that can dramatically affect one's emotions, physical and mental health. Such a condition can be caused by the environment (e.g. work-place) and external factors (e.g. excessive workload, illness or injury, personal problems), but also by internal factors (e.g., negative emotions, negative thoughts, insecurities, etc.). Stress has become the illness of present times affecting people regardless the gender, age, or social status, and causing a reduction in the quality of life interfering with work performance and social life. Indeed, it is associated with a range of pathological conditions (e.g. cognitive, neurovascular, cardiovascular) that can arise when stress becomes a chronic state. Therefore, methodologies to reliably assess mental stress and the underlying emotional states are required to detect harmful conditions and reduce negative effects.
Neuroimaging techniques (e.g. EEG, fNIRS, MEG) and autonomic nervous system monitoring approaches (e.g. heart rate variability, breathing rate, skin conductance) have been exploited for stress detection. Multimodal approaches, which can provide a more comprehensive understanding of the interplay between central and autonomic nervous systems in this context are therefore relevant. Moreover, advances towards a reliable assessment of the mental state are essential to allow the development of paradigms aimed at facilitating positive mental state, improve subjects’ performances and prevent stressful conditions in several environments and contexts (e.g. work-place, school, neurorehabilitation). Therefore, the goal of this research topic is to investigate, in the field of cognitive neuroergonomics, the influence of internal and external factors on mental state, detect stressful conditions and propose paradigms to prevent negative psycho-physiological effects.
This research topic will consider research papers, theories, models, and applications that present neurophysiological measures to identify and monitor the subject’s mental state in relation to potentially stressful situation. We are interested in both research that seeks to improve our understanding of the underlying neurocognitive mechanisms in response to such conditions, and papers proposing new methodology to identify and prevent stressful situations. Thus, we welcome multidisciplinary studies that address but are not limited to the following themes:
• Neurophysiological monitoring
• Influence of external factors on the neurophysiological status
• Central nervous system monitoring via unimodal or multimodal neuroimaging, optical, or electrophysiological techniques
• Autonomic nervous system monitoring (e.g. heart rate variability, breathing rate, skin conductance)
• Real-world applications
• Multi-source data integration
• Monitoring with wearable and contactless devices
• Affective computing