ABE: An Agent-Based Software Architecture for a Multimodal Emotion Recognition Framework
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J. Gonzalez-Sanchez, M. E. Chavez-Echeagaray, R. Atkinson, W. Burleson. Arizona State University, USA
Abstract
The computer’s ability to recognize human emotional states given physiological signals is gaining in popularity to create empathetic systems such as learning environments, health care systems and videogames. Despite that, there are few frameworks, libraries, architectures, or software tools, which allow systems developers to easily integrate emotion recognition into their software projects. The work reported here offers a first step to fill this gap in the lack of frameworks and models, addressing: (a) the modeling of an agent-driven component-based architecture for multimodal emotion recognition, called ABE, and (b) the use of ABE to implement a multimodal emotion recognition framework to support third-party systems becoming empathetic systems.Click here to read the full report
J. Gonzalez-Sanchez, M. E. Chavez-Echeagaray, R. Atkinson, W. Burleson. Arizona State University, USA
Abstract
The computer’s ability to recognize human emotional states given physiological signals is gaining in popularity to create empathetic systems such as learning environments, health care systems and videogames. Despite that, there are few frameworks, libraries, architectures, or software tools, which allow systems developers to easily integrate emotion recognition into their software projects. The work reported here offers a first step to fill this gap in the lack of frameworks and models, addressing: (a) the modeling of an agent-driven component-based architecture for multimodal emotion recognition, called ABE, and (b) the use of ABE to implement a multimodal emotion recognition framework to support third-party systems becoming empathetic systems.Click here to read the full report
J. Gonzalez-Sanchez, M. E. Chavez-Echeagaray, R. Atkinson, W. Burleson. Arizona State University, USA
Abstract
The computer’s ability to recognize human emotional states given physiological signals is gaining in popularity to create empathetic systems such as learning environments, health care systems and videogames. Despite that, there are few frameworks, libraries, architectures, or software tools, which allow systems developers to easily integrate emotion recognition into their software projects. The work reported here offers a first step to fill this gap in the lack of frameworks and models, addressing: (a) the modeling of an agent-driven component-based architecture for multimodal emotion recognition, called ABE, and (b) the use of ABE to implement a multimodal emotion recognition framework to support third-party systems becoming empathetic systems.Click here to read the full report
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© 2026 EMOTIV, All rights reserved.
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*Disclaimer – EMOTIV products are intended to be used for research applications and personal use only. Our products are not sold as Medical Devices as defined in EU directive 93/42/EEC. Our products are not designed or intended to be used for diagnosis or treatment of disease.
Note on Translations: Non-English versions of this website has been translated for your convenience using artificial intelligence. While we strive for accuracy, automated translations may contain errors or nuances that differ from the original text. For the most accurate information, please refer to the English version of this site.
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Company
© 2026 EMOTIV, All rights reserved.
Your Privacy Choices (Cookie Settings)
*Disclaimer – EMOTIV products are intended to be used for research applications and personal use only. Our products are not sold as Medical Devices as defined in EU directive 93/42/EEC. Our products are not designed or intended to be used for diagnosis or treatment of disease.
Note on Translations: Non-English versions of this website has been translated for your convenience using artificial intelligence. While we strive for accuracy, automated translations may contain errors or nuances that differ from the original text. For the most accurate information, please refer to the English version of this site.