Authors:
Vincenzo Carletti
;
Antonio Greco
;
Alessia Saggese
;
Mario Vento
and
Vincenzo Vigilante
Affiliation:
University of Salerno, Italy
Keyword(s):
Fall Detection, Embedded Systems, Wereable Devices.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
Abstract:
Every year 424,000 fatal accidents occur, they are the second cause of unintentional death after road traffic
injuries. The difference between fatal and not fatal accidents often is the presence of other people able to
promptly provide first aid or call for help. Unfortunately, even during the practice of group activities (e.g.
team sports) an accident can happen when a person is alone or out of sight; thus, the availability of devices
able to detect if a serious accident is occurred and consequently arise an alarm to other people is an important
issue for the safety of people. Starting from these considerations, in this paper we propose a wearable device
able to detect accidents occurring during the practice of running. The device uses a one class SVM trained only
on the normal activity and classifies as anomalies all the unknown situations. Then, in order to avoid alarms
related to non dangerous events, the output of the classifier is analyzed by an additional stage responsible to
detect if the person is or not unconscious after an abnormal event. In the former case an alarm is arisen by the
system.
(More)