Next Article in Journal
Simultaneous-Fault Diagnosis of Gearboxes Using Probabilistic Committee Machine
Previous Article in Journal
Pressure and Temperature Sensors Using Two Spin Crossover Materials
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(2), 184; doi:10.3390/s16020184

From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

1
Instituto de Telecomunicações, University of Beira Interior, 6201-001 Covilhã, Portugal
2
Altranportugal, 1990-096 Lisbon, Portugal
3
ALLab - Assisted Living Computing and Telecommunications Laboratory, Department of Informatics, University of Beira Interior, 6201-001 Covilhã, Portugal
4
ECATI, Universidade Lusófona de Humanidades e Tecnologias, 1749-024 Lisbon, Portugal
5
Faculty of Science, Engineering and Computing, Kingston University, Kingston upon Thames KT1 2EE, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 21 November 2015 / Revised: 22 January 2016 / Accepted: 26 January 2016 / Published: 2 February 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [414 KB, uploaded 2 February 2016]   |  

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). View Full-Text
Keywords: sensor data fusion; accelerometer; data collection; signal processing; sensors signal; activities of daily living sensor data fusion; accelerometer; data collection; signal processing; sensors signal; activities of daily living
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Pires, I.M.; Garcia, N.M.; Pombo, N.; Flórez-Revuelta, F. From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices. Sensors 2016, 16, 184.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top