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Diabetic foot ulcer mobile detection system using smart phone thermal camera: a feasibility study

Overview of attention for article published in BioMedical Engineering OnLine, October 2017
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)
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3 X users

Citations

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78 Dimensions

Readers on

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220 Mendeley
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Title
Diabetic foot ulcer mobile detection system using smart phone thermal camera: a feasibility study
Published in
BioMedical Engineering OnLine, October 2017
DOI 10.1186/s12938-017-0408-x
Pubmed ID
Authors

Luay Fraiwan, Mohanad AlKhodari, Jolu Ninan, Basil Mustafa, Adel Saleh, Mohammed Ghazal

Abstract

Nowadays, the whole world is being concerned with a major health problem, which is diabetes. A very common symptom of diabetes is the diabetic foot ulcer (DFU). The early detection of such foot complications can protect diabetic patients from any dangerous stages that develop later and may require foot amputation. This work aims at building a mobile thermal imaging system that can be used as an indicator for possible developing ulcers. The proposed system consists of a thermal camera connected to a Samsung smart phone, which is used to acquire thermal images. This thermal imaging system has a simulated temperature gradient of more than 2.2 °C, which represents the temperature difference (in the literature) than can indicate a possible development of ulcers. The acquired images are processed and segmented using basic image processing techniques. The analysis and interpretation is conducted using two techniques: Otsu thresholding technique and Point-to-Point mean difference technique. The proposed system was implemented under MATLAB Mobile platform and thermal images were analyzed and interpreted. Four testing images (feet images) were used to test this procedure; one image with any temperature variation to the feet, and three images with skin temperature increased to more than 2.2 °C introduced at different locations. With the two techniques applied during the analysis and interpretation stage, the system was successful in identifying the location of the temperature increase. This work successfully implemented a mobile thermal imaging system that includes an automated method to identify possible ulcers in diabetic patients. This may give diabetic patients the ability for a frequent self-check of possible ulcers. Although this work was implemented in simulated conditions, it provides the necessary feasibility to be further developed and tested in a clinical environment.

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The data shown below were collected from the profiles of 3 X users 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 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 220 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 35 16%
Student > Master 25 11%
Researcher 19 9%
Student > Ph. D. Student 16 7%
Student > Doctoral Student 14 6%
Other 35 16%
Unknown 76 35%
Readers by discipline Count As %
Engineering 36 16%
Nursing and Health Professions 31 14%
Medicine and Dentistry 25 11%
Computer Science 20 9%
Biochemistry, Genetics and Molecular Biology 3 1%
Other 20 9%
Unknown 85 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 February 2021.
All research outputs
#7,541,834
of 23,008,860 outputs
Outputs from BioMedical Engineering OnLine
#212
of 824 outputs
Outputs of similar age
#122,526
of 323,055 outputs
Outputs of similar age from BioMedical Engineering OnLine
#4
of 11 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% 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 4.7. This one has gotten more attention than average, scoring higher than 62% of its peers.
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 323,055 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
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 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.