Browsing by Author "Damasevicius, Robertas"
Now showing 1 - 1 of 1
- Results Per Page
- Sort Options
Article Citation - WoS: 16Citation - Scopus: 20Fusion of smartphone sensor data for classification of daily user activities(Springer, 2021) Sengul, Gokhan; Özçelik, Erol; Ozcelik, Erol; Misra, Sanjay; Damasevicius, Robertas; Maskeliunas, Rytis; 115500; PsikolojiNew mobile applications need to estimate user activities by using sensor data provided by smart wearable devices and deliver context-aware solutions to users living in smart environments. We propose a novel hybrid data fusion method to estimate three types of daily user activities (being in a meeting, walking, and driving with a motorized vehicle) using the accelerometer and gyroscope data acquired from a smart watch using a mobile phone. The approach is based on the matrix time series method for feature fusion, and the modified Better-than-the-Best Fusion (BB-Fus) method with a stochastic gradient descent algorithm for construction of optimal decision trees for classification. For the estimation of user activities, we adopted a statistical pattern recognition approach and used the k-Nearest Neighbor (kNN) and Support Vector Machine (SVM) classifiers. We acquired and used our own dataset of 354 min of data from 20 subjects for this study. We report a classification performance of 98.32 % for SVM and 97.42 % for kNN.