AUBADE: A Telemedicine Platform for Assessing Emotions
Author Information
Author(s): Katsis Christos D, Ganiatsas George, Fotiadis Dimitrios I
Primary Institution: University of Ioannina
Hypothesis
Can an integrated telemedicine platform accurately assess affective physiological states in individuals?
Conclusion
The AUBADE system can classify emotional states with an accuracy of 86.0% using physiological signals.
Supporting Evidence
- The AUBADE system classifies emotions into five categories: high stress, low stress, disappointment, euphoria, and neutral.
- The system has been validated using data from four drivers in simulated race conditions.
- AUBADE's classification accuracy is based on a dataset created from expert annotations every 10 seconds.
Takeaway
AUBADE is a system that helps understand how people feel by measuring their body's responses, like heart rate and muscle activity.
Methodology
The system uses biosensors to collect data on facial electromyogram, respiration, electrodermal activity, and electrocardiogram to classify emotions.
Limitations
The system's effectiveness in real-world conditions is still unknown, and it requires extensive testing.
Participant Demographics
Participants included car racing drivers and patients with neurological disorders.
Digital Object Identifier (DOI)
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