Human activity data discovery from triaxial accelerometer sensor: Non-supervised learning sensitivity to feature extraction parametrization. Issue 2 (March 2015) - Machado, Inês P.; Luísa Gomes, A.; Gamboa, Hugo; Paixão, Vítor; Costa, Rui M.
Highlights The presented study performs two different tests in intra and inter subject context. A set of 180 features is implemented to be selected based on clustering performance. Our algorithm searches for the best feature extraction parameter. A new clustering metric based on the construction of the confusion matrix is proposed. A novel gesture recognition system based on data from a single 3 dimensional accelerometer.