“…The obtained sensor data is partitioned into multiple segments in order to map them to the activity descriptions known as activity segmentation, where a segment is a consecutive sequence of time instants during which an activity is performed [6]. Activity segmentation is performed using different techniques, sliding windows [7], relative weighting of objects in adjacent activities [8] or pattern mining [9], just to name a few. Segmented activity instances are classified in activity classes using different learning models such as Hidden Markov Model (HMM) [10], Conditional Random Fields (CRF) [11], Naive Bayes (NB) [12], Support Vector Machine (SVM) [13], Artificial Neural Network (ANN) [14,15], and Decision Tree (DT) [16].…”