Regions of interest selection and thermal imaging data analysis in sports and exercise science: a narrative review

Abstract

Objective: Infrared thermography (IRT) is a non-invasive, contactless and low-cost technology that allows recording of the radiating energy that is released from a body, providing an estimate of its superficial temperature. Thanks to the improvement of infrared thermal detectors, this technique is widely used in the biomedical field to monitor the skin temperature for different purposes (e.g. assessing circulatory diseases, psychophysiological state, affective computing). Particularly, in sports and exercise science, thermography is extensively used to assess sports performance, to investigate superficial vascular changes induced by physical exercise, and to monitor injuries. However, the methods of analysis employed to treat IRT data are not standardized, and hence introduce variability in the results. Approach: This review focuses on the methods of analysis currently used for thermal imaging in sports and exercise science. Main Results: Firstly, the procedures employed for the selection of regions of interest (ROIs) from anatomical body districts are reviewed, paying attention also to the potentialities of morphing algorithms to increase the reproducibility of thermal results. Secondly, the statistical approaches utilized to characterize the temperature frequency and spatial distributions within ROIs are investigated, showing their strengths and weaknesses. Moreover, the importance of employing tracking methods to analyze the temporal thermal oscillations within ROIs is discussed. Thirdly, the capability of employing procedures of investigation based on machine learning frameworks on thermal imaging in sports science is examined. Significance: Finally, some proposals to improve the standardization and the reproducibility of IRT data analysis are provided, in order to facilitate the development of a common database of thermal images and to improve the effectiveness of IRT in sports science.

Central and Peripheral Thermal Signatures of Brain-Derived Fatigue during Unilateral Resistance Exercise: A Preliminary Study

“…Hence, such a metric is sensitive to a cumulative effect of both exercise and the recovery phase, characterized by an initial vasoconstriction followed by a vasodilation, respectively [ 12 ]. However, the effectiveness of other metrics indicative of the skin temperature response to exercised limb, and of different statistical indices describing skin temperature distribution, should be further explored within the same experimental paradigm [ 35 ].…”

Preliminary study of thermal density distribution and entropy analysis during cycling exercise stress test using infrared thermography

“…Current reports using infrared thermography during exercise have primarily focused on measuring absolute body temperature. However, these attempts have demonstrated limited effectiveness, and almost no significant correlations have been found with physiological parameters 1 , 14 . In the current study, we found no statistical changes in surface temperatures during the incremental exercise test.…”

Theory and applications of InfraRed and thermal image analysis in ergonomics research

“…When an IR image is captured, it does not differentiate between the region of interest (ROI) and the background. Various techniques have been used to capture the ROI, either manually or automatically, depending on the distance between the IR equipment and the participant (Barcelos et al, 2014;Quesada, 2017;Perpetuini et al, 2021). After obtaining the necessary images, qualitative and quantitative approaches are used for their interpretation.…”