Sistema de Detección de Caídas basado en Celulares Inteligentes (Smartphone-based Human Fall Detection System)

Luis Valcourt (luis.valcourt@upr.edu)1, Yueng De La Hoz (ysdelahoz@gmail.com)2, Miguel Labrador (mlabrador@usf.edu)2


1Universidad de Puerto Rico en Bayamón
2University of South Florida

This paper appears in: Revista IEEE América Latina

Publication Date: Feb. 2016
Volume: 14,   Issue: 2 
ISSN: 1548-0992


Abstract:
The use of technology has proven to be a value asset in the health department. Nowadays, from computers to smartphones, technology helps people in their activities, being these personally or cooperativily. Thanks to these advantages, new research has develop to create systems and applications to help with people's health, in our case detecting fall accidents with the use of smartphones. This paper presents an approach to detect falls using different proposed algorithms with the goal of helping people with their health and security. The system es composed of three different components: data collection, location selection, and fall detection. It utilizes the smartphone's built-in sensors (accelerometer, gyroscope) to identify the location of the smartphone in the user's body (chest, pocket, holster, etc.) and once a location is identified, the fall detection component takes place. A general description on fall detection systems is provided, including the different types of sensors used nowadays. The proposed solution is presented and described in great detail. A total accuracy of 81.3% was calculated from the fall detection proposed algorithm. The top three locations to detect a fall were: texting with a 95.8% fall detection accuracy, pants' side pocket with an 87.5% accuracy, and shirt chest pocket with an 83.3% accuracy. Also an extra study was done using only the holster location generating an excellent 100% location selection accuracy

Index Terms:
Accelerometer, gyroscope, fall detection, location selection, mobile applications   


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