Principal Investigator: Dr Owen Falzon, Centre for Biomedical Cybernetics
Co-Investigator: Mr Jean Gauci Centre for Biomedical Cybernetics
Co-Investigator: Prof. Kenneth Camilleri, Centre for Biomedical Cybernetics

Externally funded: MCST-CVP R&I-2019-012-V (2019) EUR 17,000

Diabetes is a common chronic condition in the Maltese population with a prevalence of over 9%. This places Malta in the first quartile for prevalence in Europe [3). Diabetes is a major risk factor for low perfusion to the lower limbs and the subsequent complications. Age is another major risk factor, together with sedentary lifestyles, limited mobility and bed ridden patients. To reduce the risk of developing complications due to low perfusion, frequent checks are required. However, with present technology frequent checks are difficult to perform. In this project our objective is to create a system based on dynamic thermal imaging for the assessment of blood perfusion to the lower limbs of high risk patients. This leads to the following objectives:  

 - The development of automated methods to extract temperature data from relevant regions of interest. These will allow for a much faster clinical tool for monitoring complications in the lower limbs.

- The development of innovative data analysis methods for the analysis of dynamic temperature patterns that will lead to an improved understanding and better assessment of foot condition.

- The integration of these data extraction and analysis methods with dedicated hardware for the development of a stand alone system which is easy to use and can better assist clinicians in assessing problematic foot conditions.

Through this project we aim to develop a system for an easier, faster and reliable way of assessing the health of the lower limbs of high risk patients that can be used in a clinical setting and potentially also by patients at their homes. These developments are expected to have a strong social, as well as economic impact for both the patient and the healthcare system.