Title
Fully-Wireless Sensor Insole as Non-invasive Tool for Collecting Gait Data and Analyzing Fall Risk.
Abstract
This paper presents the final results and future projection of the European project WIISEL (Wireless Insole for Independent and Safe Elderly Living), that reached to build the first full-wireless insole (that include both wireless communication and wireless charging). These insoles provide a new set of non-invasive tools that can be used either at the clinical installations or at home. That solution improves the usability and user experience compared with traditional tools (smart carpets, wired insoles, etc.) that are oriented to clinical installations. And hence, provide a powerful tool for Ambient Intelligent for Health, especially for elderly people, increasing their autonomy and providing means for long term monitoring. Health parameters analysed are fall risk and gait analysis. Both are assessed on the establishment of clinical parameters such as fall risk index, and gait pattern and fall detection and algorithms. All those can be obtained thanks to our fully-wireless flexible insole that contains the sensors, embedded processing and wireless communications and charging. Pressure and inertial sensors are embedded into the insoles and a smartphone collects data utilizing Bluetooth Low Energy that is later sent to a main server analysis for its management, analysis and storage. This provides the selected information to the corresponding platform users being either end-users/patients, their relatives or caregivers and the related clinicians.
Year
DOI
Venue
2015
10.1007/978-3-319-26508-7_2
AMBIENT INTELLIGENCE FOR HEALTH, AMIHEALTH 2015
Keywords
Field
DocType
Fall risk,Gait analysis,Wireless insole,Sensors,Bluetooth low energy,Qi wireless charging,Software tools for gait analysis,Fall risk index (FRI)
User experience design,Wireless,Gait,Simulation,Computer science,Usability,Fall risk,Gait analysis,Bluetooth Low Energy
Conference
Volume
ISSN
Citations 
9456
0302-9743
1
PageRank 
References 
Authors
0.36
0
12