Development of high-resolution infrared thermographic imaging method as a diagnostic tool for acute undifferentiated limp in young children

OWEN, Ruaridh, RAMLAKHAN, Shammi, SAATCHI, Reza and BURKE, Derek (2018). Development of high-resolution infrared thermographic imaging method as a diagnostic tool for acute undifferentiated limp in young children. Medical & biological engineering & computing, 56 (6), 1115-1125.

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Official URL: https://link.springer.com/article/10.1007%2Fs11517...
Link to published version:: https://doi.org/10.1007/s11517-017-1749-0

Abstract

Acute limp is a common presenting condition in the paediatric emergency department. There are a number of causes of acute limp that include traumatic injury, infection and malignancy. These causes in young children are not easily distinguished. In this pilot study, an infrared thermographic imaging technique to diagnose acute undifferentiated limp in young children was developed. Following required ethics approval, 30 children (mean age = 5.2 years, standard deviation = 3.3 years) were recruited. The exposed lower limbs of participants were imaged using a high-resolution thermal camera. Using predefined regions of interest (ROI), any skin surface temperature difference between the healthy and affected legs was statistically analysed, with the aim of identifying limp. In all examined ROIs, the median skin surface temperature for the affected limb was higher than that of the healthy limb. The small sample size recruited for each group, however, meant that the statistical tests of significant difference need to be interpreted in this context. Thermal imaging showed potential in helping with the diagnosis of acute limp in children. Repeating a similar study with a larger sample size will be beneficial to establish reproducibility of the results.

Item Type: Article
Uncontrolled Keywords: Thermography, limp diagnosis, limp injuries, children
Research Institute, Centre or Group: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Mobile Machine and Vision Laboratory
Departments: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
Identification Number: https://doi.org/10.1007/s11517-017-1749-0
Related URLs:
Depositing User: Reza Saatchi
Date Deposited: 08 Dec 2017 12:25
Last Modified: 16 Nov 2018 14:01
URI: http://shura.shu.ac.uk/id/eprint/17445

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