Fall Detection Using Commodity Smart Watch and Smart Phone - Artificial Intelligence Applications and Innovations (AIAI 2014)
Conference Papers Year : 2014

Fall Detection Using Commodity Smart Watch and Smart Phone

Abstract

Human motion data captured from wearable devices such as smart watches can be utilized for activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. The output of such sensors is data streams that require real-time recognition, especially in emergency situations. This paper presents a novel application that utilizes the low-cost Pebble Smart Watch together with an Android device (i.e a smart phone) and allows the efficient transmission, storage and processing of motion data. The paper includes the details of the stream data capture and processing methodology, along with an initial evaluation of the achieved accuracy in detecting falls.
Fichier principal
Vignette du fichier
978-3-662-44654-6_7_Chapter.pdf (369.74 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01391294 , version 1 (03-11-2016)

Licence

Identifiers

Cite

Ilias Maglogiannis, Charalampos Ioannou, George Spyroglou, Panayiotis Tsanakas. Fall Detection Using Commodity Smart Watch and Smart Phone. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. pp.70-78, ⟨10.1007/978-3-662-44654-6_7⟩. ⟨hal-01391294⟩
184 View
621 Download

Altmetric

Share

More