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A Multi-Stage Human Factors and Comfort Assessment of Instrumented Insoles Designed for Use in a Connected Health Infrastructure

Overview of attention for article published in Journal of Personalized Medicine, December 2015
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Title
A Multi-Stage Human Factors and Comfort Assessment of Instrumented Insoles Designed for Use in a Connected Health Infrastructure
Published in
Journal of Personalized Medicine, December 2015
DOI 10.3390/jpm5040487
Pubmed ID
Authors

Richard Harte, Leo R. Quinlan, Liam Glynn, Alejandro Rodriguez-Molinero, Thomas Scharf, Carlos Carenas, Elisenda Reixach, Joan Garcia, Jordi Carrabina, Gearóid ÓLaighin

Abstract

Wearable electronics are gaining widespread use as enabling technologies, monitoring human physical activity and behavior as part of connected health infrastructures. Attention to human factors and comfort of these devices can greatly positively influence user experience, with a subsequently higher likelihood of user acceptance and lower levels of device rejection. Here, we employ a human factors and comfort assessment methodology grounded in the principles of human-centered design to influence and enhance the design of an instrumented insole. A use case was developed and interrogated by stakeholders, experts, and end users, capturing the context of use and user characteristics for the instrumented insole. This use case informed all stages of the design process through two full design cycles, leading to the development of an initial version 1 and a later version 2 prototype. Each version of the prototype was subjected to an expert human factors inspection and controlled comfort assessment using human volunteers. Structured feedback from the first cycle of testing was the driver of design changes implemented in the version 2 prototype. This prototype was found to have significantly improved human factors and comfort characteristics over the first version of the prototype. Expert inspection found that many of the original problems in the first prototype had been resolved in the second prototype. Furthermore, a comfort assessment of this prototype with a group of young healthy adults showed it to be indistinguishable from their normal footwear. This study demonstrates the power and effectiveness of human factors and comfort assessment methodologies in influencing and improving the design of wearable devices.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 28%
Student > Ph. D. Student 9 11%
Student > Bachelor 9 11%
Researcher 6 7%
Student > Doctoral Student 5 6%
Other 9 11%
Unknown 22 27%
Readers by discipline Count As %
Engineering 15 18%
Nursing and Health Professions 9 11%
Computer Science 9 11%
Social Sciences 7 8%
Psychology 5 6%
Other 16 19%
Unknown 22 27%
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 03 January 2016.
All research outputs
#18,434,182
of 22,837,982 outputs
Outputs from Journal of Personalized Medicine
#1,715
of 2,426 outputs
Outputs of similar age
#281,664
of 390,448 outputs
Outputs of similar age from Journal of Personalized Medicine
#11
of 11 outputs
Altmetric has tracked 22,837,982 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,426 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 13th percentile – i.e., 13% 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 390,448 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.