title: Multi-sensor fusion for enhanced contextual awareness of everyday activities with ubiquitous devices.
abstract: In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.
authors.affiliation: Department of Electronic & Computer Engineering, University of Limerick, Limerick, Ireland. johnj.guiry@ul.ie.
authors.forename: John J
authors.initials: JJ
authors.lastname: Guiry
authors.affiliation: Department of Electronic & Computer Engineering, University of Limerick, Limerick, Ireland. pepijn.vandeven@ul.ie.
authors.forename: Pepijn
authors.initials: P
authors.lastname: van de Ven
authors.affiliation: Department of Electronic & Computer Engineering, University of Limerick, Limerick, Ireland. john.nelson@ul.ie.
authors.forename: John
authors.initials: J
authors.lastname: Nelson
mesh_terms: D000203:Activities of Daily Living; D000465:Algorithms; D001364:Awareness; D040421:Cell Phone; D005240:Feasibility Studies; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted