About this Research Topic
Emotions are a fundamental aspect of human experience and play a critical role in shaping our perceptions, behaviors, and decisions. For many years, researchers have studied emotions using methods such as self-report questionnaires and behavioral observations. However, traditional methods of emotion assessment have some limitations, such as biased outcomes or subjectivity.
In recent years, technological advances have led to the development of new tools and techniques that have the potential to overcome these limitations. For example, wearable devices can provide continuous monitoring of physiological signals, such as heart rate and skin conductance, as well as the electroencephalography is able to record the brain activity. Furthermore, computer vision and machine learning algorithms can analyze facial expressions and body movements to detect emotional states, while augmented and virtual reality environments can provide ecologically valid contexts for emotion elicitation.
These technologies offer exciting new opportunities for researchers in various fields, such as psychology, neuroscience, affective computing, education, interfaces design, and human-computer interaction. The development and evaluation of technologies for emotion assessment and elicitation are rapidly expanding research areas, with the potential to transform how we recognize and analyze emotions.
This research topic aims to explore the latest technologies for emotion assessment and elicitation, and their application in different fields. It aims to bring together researchers, practitioners, and professionals from diverse backgrounds to present and discuss the latest advances in technologies for emotion analysis, including but not limited to skin conductance, heart rate variability, electroencephalography, fMRI, fNIRS, facial expressions, electromyography, and eye movement.
Understanding the underlying mechanisms of these technologies is essential for ensuring their reliability, validity, and generalizability; therefore, we welcome studies that evaluate and explain how the technology assessment is performed and how these new technologies work, including their strengths and limitations.
Overall this research topic will provide a comprehensive overview of the latest research on technologies for emotion assessment and elicitation, from theoretical and conceptual advances to practical applications in different fields. We encourage researchers from diverse backgrounds and disciplines to submit their original work to this research topic and contribute to advancing the field of emotion assessment.
This research topic welcomes original research articles, reviews, and empirical studies that provide insights into the design, development, use, and validation of technologies for emotion assessment and elicitation. Contributions that focus on both physiological and behavioral aspects of emotions are welcome. Potential authors are encouraged to submit papers that address, but are not limited to, the following topics:
• Novel methods and tools for emotion assessment and elicitation
• Practical advances in the measurement and interpretation of emotions using techhnology
• Wearable devices for physiological signal monitoring in emotion analysis
• Multimodal interaction of technologies for emotion analysis
• Evaluation of the reliability and usability of emotion assessment technologies
• Integration of multiple data for improved emotion recognition accuracy
• Augmented and virtual reality environments for enhanced ecological validity
• Affective computing research and applications
• Machine learning algorithms for emotion recognition
• Statistical learning and inference to improve understanding of the emotional process
We encourage submissions that contribute to the development, application, interaction and evaluation of new methods and tools for measuring emotions in different settings. Also, investigations that contribute to our understanding of the synergistic use of multimodal data and their correlation to effectively decode emotions.
In recent years, technological advances have led to the development of new tools and techniques that have the potential to overcome these limitations. For example, wearable devices can provide continuous monitoring of physiological signals, such as heart rate and skin conductance, as well as the electroencephalography is able to record the brain activity. Furthermore, computer vision and machine learning algorithms can analyze facial expressions and body movements to detect emotional states, while augmented and virtual reality environments can provide ecologically valid contexts for emotion elicitation.
These technologies offer exciting new opportunities for researchers in various fields, such as psychology, neuroscience, affective computing, education, interfaces design, and human-computer interaction. The development and evaluation of technologies for emotion assessment and elicitation are rapidly expanding research areas, with the potential to transform how we recognize and analyze emotions.
This research topic aims to explore the latest technologies for emotion assessment and elicitation, and their application in different fields. It aims to bring together researchers, practitioners, and professionals from diverse backgrounds to present and discuss the latest advances in technologies for emotion analysis, including but not limited to skin conductance, heart rate variability, electroencephalography, fMRI, fNIRS, facial expressions, electromyography, and eye movement.
Understanding the underlying mechanisms of these technologies is essential for ensuring their reliability, validity, and generalizability; therefore, we welcome studies that evaluate and explain how the technology assessment is performed and how these new technologies work, including their strengths and limitations.
Overall this research topic will provide a comprehensive overview of the latest research on technologies for emotion assessment and elicitation, from theoretical and conceptual advances to practical applications in different fields. We encourage researchers from diverse backgrounds and disciplines to submit their original work to this research topic and contribute to advancing the field of emotion assessment.
This research topic welcomes original research articles, reviews, and empirical studies that provide insights into the design, development, use, and validation of technologies for emotion assessment and elicitation. Contributions that focus on both physiological and behavioral aspects of emotions are welcome. Potential authors are encouraged to submit papers that address, but are not limited to, the following topics:
• Novel methods and tools for emotion assessment and elicitation
• Practical advances in the measurement and interpretation of emotions using techhnology
• Wearable devices for physiological signal monitoring in emotion analysis
• Multimodal interaction of technologies for emotion analysis
• Evaluation of the reliability and usability of emotion assessment technologies
• Integration of multiple data for improved emotion recognition accuracy
• Augmented and virtual reality environments for enhanced ecological validity
• Affective computing research and applications
• Machine learning algorithms for emotion recognition
• Statistical learning and inference to improve understanding of the emotional process
We encourage submissions that contribute to the development, application, interaction and evaluation of new methods and tools for measuring emotions in different settings. Also, investigations that contribute to our understanding of the synergistic use of multimodal data and their correlation to effectively decode emotions.
Keywords: Emotion assessment, Affective elicitacion, Biometrics, Physiological data; Neuroscience, Affective computing, AR/VR, HCI, BCI
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
