Integration of a Mobile Application using Medical Infrared Imaging to improve the Effectiveness of Physiotherapy Treatments
Medical Infrared thermography (MIT) has been identified as a promising solution to locate inflammation within the human body. Infrared thermography is a non-radiating and non-invasive method which provides information about physiological functions related to the mapping of the body’s thermal radiation. In this project, we investigate the use of a mobile phone combined with a low cost, high resolution infrared camera and the advanced image processing toolbox from MATLAB® as a basic diagnostic tool for location and detection of thermal abnormalities (abnormally high or low body surface temperature) in musculoskeletal conditions.
The three aims of this project are: First, to design a functional thermal imaging mobile application for patient rehabilitation and therapy assessment. Second, to use pre and post treatment thermal images to assess the effectiveness of the therapy. Finally, to use deep learning techniques to simplify the process of identifying abnormalities by automatically learning similarities and differences of features within images to predict the best treatment for future patients.
In this paper the development of the mobile app as a proof of concept is reported with the future aim to use deep learning algorithms. The application will be used to help physiotherapists in NHS Tayside (Scotland) to enhance their best practice.