Toward User-Independent Emotion Recognition Using Physiological Signals

Many techniques have been developed to improve the flexibility and the fit of detection models beyond user-dependent models, yet detection tasks continue to be complex and challenging. For emotion, which is known to be highly user-dependent, improvements to the emotion learning algorithm can greatly...

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Autores:

Tipo de recurso:

Fecha de publicación:

2019

Institución:

Universidad de Medellín

Repositorio:

Repositorio UDEM

Idioma:

eng

OAI Identifier:

oai:repository.udem.edu.co:11407/5711

Acceso en línea:

http://hdl.handle.net/11407/5711

Palabra clave:

Emotion recognition
ensemble learning
multi-dimensional dynamic time warping (MD-DTW)
optimization
physiological signals
Biological systems
Electrocardiography
Electromyography
Learning algorithms
Nearest neighbor search
Optimization
Physiology
Psychology computing
Sensor data fusion
Sensors
Speech recognition
Support vector machines
Biological system modeling
Emotion recognition
Ensemble learning
Multi-dimensional dynamics
Physiological signals
Biomedical signal processing

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http://purl.org/coar/access_right/c_16ec