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Fully-wireless sensor insole as non-invasive tool for collecting gait data and analyzing fall risk
Autonomous University of Barcelona, Spain.
Autonomous University of Barcelona, Spain.
RISE, Swedish ICT, Acreo.
RISE, Swedish ICT, Acreo.ORCID iD: 0000-0002-0459-1157
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2015 (English)In: Ambient Intelligence for Health / [ed] José Bravo, Ramón Hervás, Vladimir Villarreal, 2015, Vol. 9456, p. 15-25Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2015. Vol. 9456, p. 15-25
Series
Lecture Notes in Computer Science (LNCS), ISSN ‎0302-9743 ; 9456
Keywords [en]
Bluetooth low energy, Fall risk, Fall risk index (FRI), Gait analysis, Qi wireless charging, Sensors, Software tools for gait analysis, Wireless insole, Artificial intelligence, Bluetooth, Digital storage, Health, Health risks, Human computer interaction, Inductive power transmission, Information management, Pattern recognition, Wireless telecommunication systems, Ambient intelligent, Bluetooth low energies (BTLE), Clinical parameters, Embedded processing, Long term monitoring, Wireless charging, Wireless communications, Risk assessment
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-35480DOI: 10.1007/978-3-319-26508-7_2Scopus ID: 2-s2.0-84954149821ISBN: 978-3-319-26507-0 (print)ISBN: 978-3-319-26508-7 (electronic)OAI: oai:DiVA.org:ri-35480DiVA, id: diva2:1258048
Conference
1st International Conference on Ambient Intelligence for Health (AmIHEALTH 2015), December 1-4, 2015, Puerto Varas, Chile
Available from: 2018-10-23 Created: 2018-10-23 Last updated: 2019-07-11Bibliographically approved

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Rusu, Cristina

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