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Accuracy (mean and standard deviation) results from the evaluation of the feature fusion model for the (a) ideal-placement, (b) self-placement and (c–f) induced-displacement (number of sensors) settings. The top legend identifies the classification paradigm. The horizontal axis labels identify the feature set used for each experiment. The activity recognition dataset (i.e., the number of activities) used is respectively underlined.
