Key result
A wearable biosignal system using support vector machines achieved a 79.3% overall classification rate for identifying emotional states in simulated car-racing drivers.
Population
10 subjects in simulated car-racing conditions
Design
Other
Authors
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Hypothesis-generating for wearable biosignal emotion detection in simulations; prospective real-world validation required before any application.
Absolute Event Rate: 79.3% vs 76.7%
A wearable multisensorial system using biosignals can classify emotional states in simulated car-racing drivers with up to 79.3% accuracy.
Katsis et al. (2008) studied Emotion recognition in car-racing drivers (n=10). Wearable system for emotion recognition (SVM classification) vs. ANFIS classification was evaluated on Overall classification rates for emotional states. A wearable biosignal system using support vector machines achieved a 79.3% overall classification rate for identifying emotional states in simulated car-racing drivers.
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