The autonomic nervous system regulates involuntary physiologic processes like heart rate, blood pressure, respiration, and digestion. Its sympathetic division prepares the body for acute stressful situations enabling fight or flight, and the parasympathetic division conserves and restores. Autonomic responses have helped us understand the subjective feelings of physical or psychological stress in a measurable way, which could be further developed into monitoring tools for specific usage scenarios. For example, the surgical stress index, which is derived from the photoplethysmographic waveform amplitude and the heart beat-to-beat interval, quantifies the physiological, hemodynamic, and sympathetic stress reactions that occur during general anesthesia caused by nociception. Compared to scenarios with a single known stressor, disentangling autonomic response patterns from multiple stressors is more challenging in both acute and chronic situations.
This Research Topic aims to collect updated knowledge on stressor-specific brain and autonomic response patterns for stress recognition close to real-life. Recent works have integrated interdisciplinary techniques and comprehensive measurement linking brain and body systems. Therefore, as a path to the goal, we are also interested in recent advances in neuroimaging, physiology, pattern mining, and pattern analysis techniques for understanding the interactions between stress, brain, and body. The specific stressors could be physical, emotional, mental, or psychosocial ones induced in lab environments or reported from real scenarios. Discussions on the differences and commonalities in the continuous impact of different chronic stressors on the autonomic nervous system are also welcome.
For this Research Topic, we encourage submissions that compare different stressors that may occur in different scenarios or are interchangeable in the same scene. Thus, we will consider experimental paradigms, cross-dataset analysis, meta-analysis, and review papers. Authors are also encouraged to submit signal processing and pattern analysis papers, serving for more accurate brain images or physiological time-series pattern recognition in the context of stress recognition.
The autonomic nervous system regulates involuntary physiologic processes like heart rate, blood pressure, respiration, and digestion. Its sympathetic division prepares the body for acute stressful situations enabling fight or flight, and the parasympathetic division conserves and restores. Autonomic responses have helped us understand the subjective feelings of physical or psychological stress in a measurable way, which could be further developed into monitoring tools for specific usage scenarios. For example, the surgical stress index, which is derived from the photoplethysmographic waveform amplitude and the heart beat-to-beat interval, quantifies the physiological, hemodynamic, and sympathetic stress reactions that occur during general anesthesia caused by nociception. Compared to scenarios with a single known stressor, disentangling autonomic response patterns from multiple stressors is more challenging in both acute and chronic situations.
This Research Topic aims to collect updated knowledge on stressor-specific brain and autonomic response patterns for stress recognition close to real-life. Recent works have integrated interdisciplinary techniques and comprehensive measurement linking brain and body systems. Therefore, as a path to the goal, we are also interested in recent advances in neuroimaging, physiology, pattern mining, and pattern analysis techniques for understanding the interactions between stress, brain, and body. The specific stressors could be physical, emotional, mental, or psychosocial ones induced in lab environments or reported from real scenarios. Discussions on the differences and commonalities in the continuous impact of different chronic stressors on the autonomic nervous system are also welcome.
For this Research Topic, we encourage submissions that compare different stressors that may occur in different scenarios or are interchangeable in the same scene. Thus, we will consider experimental paradigms, cross-dataset analysis, meta-analysis, and review papers. Authors are also encouraged to submit signal processing and pattern analysis papers, serving for more accurate brain images or physiological time-series pattern recognition in the context of stress recognition.
