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Activity Recognition Chain (ARC). Raw data are firstly acquired from sensors. After pre-processing, segments of data are extracted (Segmentation) and values relevant to the recognition problem are computed from them (Feature extraction). A classifier is then trained and evaluated using those features (Classification). In our framework, all steps of the ARC—except the feature extraction part—are fixed, and a Support-Vector-Machine (SVM) classifier is used for the classification stage.
