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Communication dans un congrès
Effect of Motion Artifact on Digital Camera Based Heart Rate Measurement
Abstract : Depression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. The proposed framework achieved a precision of 94.8% for detecting persons achieving high scores on a self-report scale of depressive symptomatology. Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation.
Keywords :
Motion artifacts
Heart rate
Lighting
Skin
Digital cameras
Face
Databases
Cameras
Cardiology
Patient monitoring
Photoplethysmography
Digital camera
remote health monitoring
Biomedical technology
Heart rate measurement method
Photoplethysmography signal
MAHNOB-HCI database
Biomedical measurement
Motion artifact effect
https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01628324
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : vendredi 3 novembre 2017 - 11:35:27
Dernière modification le : lundi 10 août 2020 - 16:24:03
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : vendredi 3 novembre 2017 - 11:35:27
Dernière modification le : lundi 10 août 2020 - 16:24:03