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.
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.70-78, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_7〉
https://hal.inria.fr/hal-01391294
Contributeur : Hal Ifip
<>
Soumis le : jeudi 3 novembre 2016 - 10:51:22
Dernière modification le : vendredi 1 décembre 2017 - 01:16:37
Document(s) archivé(s) le : samedi 4 février 2017 - 13:07:12
Ilias Maglogiannis, Charalampos Ioannou, George Spyroglou, Panayiotis Tsanakas. Fall Detection Using Commodity Smart Watch and Smart Phone. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.70-78, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_7〉. 〈hal-01391294〉
