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Open AccessArticle

Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices

1
Instituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
2
Altranportugal, 1990-096 Lisbon, Portugal
3
ALLab—Assisted Living Computing and Telecommunications Laboratory, Computing Science Department, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
4
ECATI, Universidade Lusófona de Humanidades e Tecnologias, 1749-024 Lisbon, Portugal
5
Department of Computer Technology, Universidad de Alicante, 03690 Sant Vicent del Raspeig, Alicante, Spain
6
Department of Information Engineering, Marche Polytechnic University, 60121 Ancona, Italy
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(2), 640; https://doi.org/10.3390/s18020640
Received: 7 January 2018 / Revised: 18 February 2018 / Accepted: 19 February 2018 / Published: 21 February 2018
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking into account several concepts, including data acquisition, data processing, data fusion, and pattern recognition. These concepts can be mapped onto different modules of the framework. The proposed framework should perform the identification of ADL without Internet connection, performing these tasks locally on the mobile device, taking in account the hardware and software limitations of these devices. The main purpose of this paper is to present a new approach for the creation of a framework for the recognition of ADL, analyzing the allowed sensors available in the mobile devices, and the existing methods available in the literature. View Full-Text
Keywords: Activities of Daily Living (ADL); environment; sensors; mobile devices; framework; data acquisition; data processing; data fusion; pattern recognition; machine learning Activities of Daily Living (ADL); environment; sensors; mobile devices; framework; data acquisition; data processing; data fusion; pattern recognition; machine learning
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Pires, I.M.; Garcia, N.M.; Pombo, N.; Flórez-Revuelta, F.; Spinsante, S. Approach for the Development of a Framework for the Identification of Activities of Daily Living Using Sensors in Mobile Devices. Sensors 2018, 18, 640.

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