Neurophysiological conditions, such as stress, anxiety and emotional state, and mental workload, can affect both physical and cognitive functions. This scenario suggests that human behavior is the result of a deep interconnection between brain and autonomic nervous system functionalities. Thanks to advancements in technological and data analytics tools, non-invasive and real-time monitoring of human central and autonomic nervous systems’ activity is allowed, enabling a quantification of the link between physiology and human performance. In particular, the assessment of the human neurophysiological condition and mental workload can be performed by mobile neuroimaging devices (e.g. EEG and fNIRS) and contactless or wearable instrumentations (e.g. infrared and RGB cameras, smartwatches), but also by means of psychological tests (e.g. NASA-TLX and STAI-Y).
Whole system monitoring of physiological functions allows the possibility to increase human performances in several fields, in accordance with the sense–assess–augment paradigm. “Sense” consists of measuring physiological signals from the human body and the surrounding environment, whereas “assess” is the data-analysis of the acquired signals, and “augment” relies on the employment of techniques and tools to modulate performance. The application of this paradigm is relevant in several fields, such as sports science, neurorehabilitation, automotive and the design of workplaces. Human performance is defined based on the population and the environment being studied. In light of this, an ergonomic approach could be beneficial for athletes in preparation of a competition, to enhance workers’ health, to improve drivers’ and pilots’ safety, to ameliorate rehabilitative outcomes, and, generally, to promote human well-being.
In this context, this Research Topic has the goal of collecting recent advances in the assessment of the neurophysiological status and mental workload, emphasizing the influence of physiological condition on physical and cognitive performances. The Topic welcomes multidisciplinary perspectives (e.g., neuroimaging, physiological, cognitive, psychological, morphological) and original Research, Systematic Reviews and Meta-analysis, Literature review, Mini-review, Methods, and Perspective articles. Topics that cover, but not limited to, the following domains are encouraged:
• The role of the neurophysiological status and mental workload in sports performances
• Affective computing (e.g. facial expressions, gesture analysis)
• Wearable and portable neuroimaging techniques (e.g. EEG and fNIRS)
• Autonomic nervous system monitoring (e.g. heart rate variability, breathing rate, infrared imaging)
• The effect of the neurophysiological status and mental workload to improve neurorehabilitation outcomes
• Real-world applications
• Workload and neurophysiological assessment in automotive and avionics
• Machine learning and Artificial Intelligence
Neurophysiological conditions, such as stress, anxiety and emotional state, and mental workload, can affect both physical and cognitive functions. This scenario suggests that human behavior is the result of a deep interconnection between brain and autonomic nervous system functionalities. Thanks to advancements in technological and data analytics tools, non-invasive and real-time monitoring of human central and autonomic nervous systems’ activity is allowed, enabling a quantification of the link between physiology and human performance. In particular, the assessment of the human neurophysiological condition and mental workload can be performed by mobile neuroimaging devices (e.g. EEG and fNIRS) and contactless or wearable instrumentations (e.g. infrared and RGB cameras, smartwatches), but also by means of psychological tests (e.g. NASA-TLX and STAI-Y).
Whole system monitoring of physiological functions allows the possibility to increase human performances in several fields, in accordance with the sense–assess–augment paradigm. “Sense” consists of measuring physiological signals from the human body and the surrounding environment, whereas “assess” is the data-analysis of the acquired signals, and “augment” relies on the employment of techniques and tools to modulate performance. The application of this paradigm is relevant in several fields, such as sports science, neurorehabilitation, automotive and the design of workplaces. Human performance is defined based on the population and the environment being studied. In light of this, an ergonomic approach could be beneficial for athletes in preparation of a competition, to enhance workers’ health, to improve drivers’ and pilots’ safety, to ameliorate rehabilitative outcomes, and, generally, to promote human well-being.
In this context, this Research Topic has the goal of collecting recent advances in the assessment of the neurophysiological status and mental workload, emphasizing the influence of physiological condition on physical and cognitive performances. The Topic welcomes multidisciplinary perspectives (e.g., neuroimaging, physiological, cognitive, psychological, morphological) and original Research, Systematic Reviews and Meta-analysis, Literature review, Mini-review, Methods, and Perspective articles. Topics that cover, but not limited to, the following domains are encouraged:
• The role of the neurophysiological status and mental workload in sports performances
• Affective computing (e.g. facial expressions, gesture analysis)
• Wearable and portable neuroimaging techniques (e.g. EEG and fNIRS)
• Autonomic nervous system monitoring (e.g. heart rate variability, breathing rate, infrared imaging)
• The effect of the neurophysiological status and mental workload to improve neurorehabilitation outcomes
• Real-world applications
• Workload and neurophysiological assessment in automotive and avionics
• Machine learning and Artificial Intelligence
