2012
DOI: 10.1016/j.intcom.2012.04.003
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A survey of methods for data fusion and system adaptation using autonomic nervous system responses in physiological computing

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Cited by 157 publications
(177 citation statements)
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“…Since the film clips were approximately one minute long, the data formed temporal sequences. In affective computing, the feature-based approach to time sequence classification dominates (Novak et al 2012). We also found this method to be more suitable for a number of reasons.…”
Section: Data Mining and Extraction Of Featuresmentioning
confidence: 99%
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“…Since the film clips were approximately one minute long, the data formed temporal sequences. In affective computing, the feature-based approach to time sequence classification dominates (Novak et al 2012). We also found this method to be more suitable for a number of reasons.…”
Section: Data Mining and Extraction Of Featuresmentioning
confidence: 99%
“…With these algorithms, we would create prediction models for classification of psychological states. Five classification methods frequently used in affective computing (Novak et al 2012) were evaluated. K-nearest neighbor (kNN) is a simple algorithm that performs instance-based learning classifying an object based on the classes of its neighbors.…”
Section: Classification Algorithmsmentioning
confidence: 99%
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