Tracking the injury recovery of professional football players with infrared thermography: Preliminary Study

Abstract

Infrared thermography is a non-invasive method of translating and viewing the radiating heat from the target surface collected by the infrared sensor into temperature as a digital image. Infrared thermography contains very useful data, especially for medical reasons. However, it has been accepted just recently. Although its usage is still questioned in sports medicine, recent studies claimed that infrared thermography can be used to examine muscle problems, injuries, and joint problems, etc. Sports medicine, physiotherapists, and medical imaging have vital importance for football teams and its’ success. During a season football teams lose a lot of matches because of the high rate of injury. That is why preventing an injury has more importance for a football team than healing an existing injury. In consequence physiotherapists use many methods to prevent football players from being injured and monitorise the injury such as creatine kinase tests, muscle strength measurements, MRI, etc. However, these methods are either not enough successful or expensive. In our study, we have developed an image processing software to examine lower extremities muscle problems of football players when they occur and after they rested a day. With this software, we aim to help physiotherapists to regulate rehabilitation plan and decide when to end the rehabilitation. Thanks to this, physiotherapists can decide to rest the football players or start treatment so that they will not get injured unnecessarily and will have a lower risk of injury. Thorough this the success of the football teams will increase because the football players will not miss matches because of the extreme training or overlooked injuries. In our proposed method, with infrared thermography, 3 football players with documented injuries were observed. They have studied again after the football players rested for 1 day and the findings were analyzed. For that the thermographic color palette’s RGB values are calculated in such a way that the upper and lower color values are discovered. In the next step, a binary mask is created, and this mask is blended with the grayscale original image, and the areas with muscle problems are displayed colored so that the physiotherapists can detect and examine problems easier. In the results part, it is shown that the areas are detected better than the human eye. It is concluded that with the help of the image processing algorithm muscle problems are detected successfully and the healing process after the resting is observed.