From data acquisition to data fusion : a comprehensive review and a roadmap for the identification of activities of daily living using mobile devices

Pires, Ivan Miguel, Garcia, Nuno M., Pombo, Nuno and Florez-Revuelta, Francisco (2016) From data acquisition to data fusion : a comprehensive review and a roadmap for the identification of activities of daily living using mobile devices. Sensors, 16(2), p. 184. ISSN (online) 1424-8220

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Abstract

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs).

Item Type: Article
Additional Information: This work was supported by the FCT project UID/EEA/50008/2013 (Este trabalho foi suportado pelo projecto FCT UID/EEA/50008/2013). The authors would also like to acknowledge the contribution of the COST Action IC1303–AAPELE - Architectures, Algorithms and Protocols for Enhanced Living Environments
Uncontrolled Keywords: accelerometer, sensor data fusion, activities of daily living, signal processing, data collection, sensors signal
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing (until 2017)
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Depositing User: Francisco Florez Revuelta
Date Deposited: 08 Apr 2016 10:46
Last Modified: 06 May 2016 10:36
DOI: https://doi.org/10.3390/s16020184
URI: http://eprints.kingston.ac.uk/id/eprint/34109

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