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Design, implementation and validation of a novel open framework for agile development of mobile health applications

Overview of attention for article published in BioMedical Engineering OnLine, August 2015
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1 X user

Citations

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230 Dimensions

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320 Mendeley
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Title
Design, implementation and validation of a novel open framework for agile development of mobile health applications
Published in
BioMedical Engineering OnLine, August 2015
DOI 10.1186/1475-925x-14-s2-s6
Pubmed ID
Authors

Oresti Banos, Claudia Villalonga, Rafael Garcia, Alejandro Saez, Miguel Damas, Juan A Holgado-Terriza, Sungyong Lee, Hector Pomares, Ignacio Rojas

Abstract

The delivery of healthcare services has experienced tremendous changes during the last years. Mobile health or mHealth is a key engine of advance in the forefront of this revolution. Although there exists a growing development of mobile health applications, there is a lack of tools specifically devised for their implementation. This work presents mHealthDroid, an open source Android implementation of a mHealth Framework designed to facilitate the rapid and easy development of mHealth and biomedical apps. The framework is particularly planned to leverage the potential of mobile devices such as smartphones or tablets, wearable sensors and portable biomedical systems. These devices are increasingly used for the monitoring and delivery of personal health care and wellbeing. The framework implements several functionalities to support resource and communication abstraction, biomedical data acquisition, health knowledge extraction, persistent data storage, adaptive visualization, system management and value-added services such as intelligent alerts, recommendations and guidelines. An exemplary application is also presented along this work to demonstrate the potential of mHealthDroid. This app is used to investigate on the analysis of human behavior, which is considered to be one of the most prominent areas in mHealth. An accurate activity recognition model is developed and successfully validated in both offline and online conditions.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 320 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 318 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 49 15%
Student > Ph. D. Student 46 14%
Student > Bachelor 31 10%
Researcher 24 8%
Student > Doctoral Student 24 8%
Other 58 18%
Unknown 88 28%
Readers by discipline Count As %
Computer Science 83 26%
Engineering 38 12%
Medicine and Dentistry 24 8%
Nursing and Health Professions 19 6%
Psychology 9 3%
Other 48 15%
Unknown 99 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 August 2015.
All research outputs
#15,344,095
of 22,824,164 outputs
Outputs from BioMedical Engineering OnLine
#424
of 824 outputs
Outputs of similar age
#154,980
of 264,395 outputs
Outputs of similar age from BioMedical Engineering OnLine
#11
of 18 outputs
Altmetric has tracked 22,824,164 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 824 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,395 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.