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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity
verfasst von : Markus Kächele, Patrick Thiam, Mohammadreza Amirian, Philipp Werner, Steffen Walter, Friedhelm Schwenker, Günther Palm
Erschienen in: Engineering Applications of Neural Networks
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In this work, a method is presented for the continuous estimation of pain intensity based on fusion of bio-physiological and video features. The focus of the paper is to analyse which modalities and feature sets are suited best for the task of recognizing pain levels in a person-independent setting. A large set of features is extracted from the available bio-physiological channels (ECG, EMG and skin conductivity) and the video stream. Experimental validation demonstrates which modalities contribute the most to a robust prediction and the effects when combining them to improve the continuous estimation given unseen persons.