DSpace@Çankaya

Fusion of smartphone sensor data for classification of daily user activities

Basit öğe kaydını göster

dc.contributor.author Şengül, Gökhan
dc.contributor.author Özçelik, Erol
dc.contributor.author Misra, Sanjay
dc.contributor.author Damaševičius, Robertas
dc.contributor.author Maskeliūnas, Rytis
dc.date.accessioned 2022-05-11T10:07:42Z
dc.date.available 2022-05-11T10:07:42Z
dc.date.issued 2021-10
dc.identifier.citation Şengül, Gökhan...at all (2021). "Fusion of smartphone sensor data for classification of daily user activities", Multimedia Tools and Applications, Vol. 80, No. 24, pp. 33527-33546. tr_TR
dc.identifier.issn 1380-7501
dc.identifier.uri http://hdl.handle.net/20.500.12416/5488
dc.description.abstract New 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. © 2021, The Author(s). tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1007/s11042-021-11105-6 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Feature Fusion tr_TR
dc.subject Human Activity Recognition tr_TR
dc.subject Wearable Intelligence tr_TR
dc.title Fusion of smartphone sensor data for classification of daily user activities tr_TR
dc.type article tr_TR
dc.relation.journal Multimedia Tools and Applications tr_TR
dc.contributor.authorID 115500 tr_TR
dc.identifier.volume 80 tr_TR
dc.identifier.issue 24 tr_TR
dc.identifier.startpage 33527 tr_TR
dc.identifier.endpage 33546 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Psikoloji Bölümü tr_TR


Bu öğenin dosyaları:

Bu öğe aşağıdaki koleksiyon(lar)da görünmektedir.

Basit öğe kaydını göster