For many years, the role of thermometry was limited to systemic (core body temperature) measurements (e.g., pulmonary catheter) or its approximation using skin/mucosa (e.g., axillary, oral, or rectal) temperature measurements. With recent advances in material science and technology, thermal measurements went beyond core body temperature measurements and found their way in many medical specialties. The article consists of two primary parts. In the first part we overviewed current clinical thermal measurement technologies across two dimensions: (a) direct vs. indirect and (b) single-point vs. multiple-point temperature measurements. In the second part, we focus primarily on clinical applications in wound care, surgery, and sports medicine. The primary focus here is the thermographic imaging modality. However, other thermal modalities are included where relevant for these clinical applications. The literature review identified two primary use scenarios for thermographic imaging: inflammation-based and perfusion-based. These scenarios rely on local (topical) temperature measurements, which are different from systemic (core body temperature) measurements. Quantifying these types of diseases benefits from thermographic imaging of an area in contrast to single-point measurements. The wide adoption of the technology would be accelerated by larger studies supporting the clinical utility of thermography.

Infrared Thermography in Wound Care, Surgery, and Sports Medicine: A Review

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.

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

Influence of infrared camera model and evaluator reproducibility in the assessment of skin temperature responses to physical exercise.

The present study aimed to assess the effects of asymmetric muscle fatigue on the skin surface temperature of abdominal and back muscles. The study was based on a pre-post/follow-up design with one group and included a total of 41 subjects (22 male, 19 female; age, 22.63 ± 3.91; weight, 71.89 ± 12.97 kg; height, 173.36 ± 9.95). All the participants were asked to perform side bends in sets of 20 repetitions on a Roman chair until complete exhaustion. The pre-, post- and follow-up test (24 h after) skin surface temperatures were recorded with infrared thermography. Subjective muscle soreness and muscle fatigue were analyzed using two questionnaires. The results of the post hoc tests showed that skin temperature was statistically significantly lower in the post-tests than in the pre- and follow-up tests, but no meaningful differences existed between the pre- and follow-up tests. Asymmetric side differences were found in the post-test for the upper and lower areas of the back. Differences were also noted for the front in both the upper and lower areas. No thermographic side asymmetries were found at the pre- or follow-up measurement for either the back or the front. Our results support the potential of using thermographic skin surface temperature to monitor exercise and recovery in athletes, as well as its use in rehabilitational exercise selection.

/pdf/effects-of-unilateral-muscle-fatigue-on-thermographic-skin-15z0b26n.pdf

Effects of Unilateral Muscle Fatigue on Thermographic Skin Surface Temperature of Back and Abdominal Muscles—A Pilot Study

Diabetic foot complications have multiple adverse effects in a person’s quality of life. Yet, efficient monitoring schemes can mitigate or postpone any disorders, mainly by early detecting regions of interest. Nowadays, optical sensors and artificial intelligence (AI) tools can contribute efficiently to such monitoring processes. In this work, we provide information on the adopted imaging schemes and related optical sensors on this topic. The analysis considers both the physiology of the patients and the characteristics of the sensors. Currently, there are multiple approaches considering both visible and infrared bands (multiple ranges), most of them coupled with various AI tools. The source of the data (sensor type) can support different monitoring strategies and imposes restrictions on the AI tools that should be used with. This review provides a comprehensive literature review of AI-assisted DFU monitoring methods. The paper presents the outcomes of a large number of recently published scholarly articles. Furthermore, the paper discusses the highlights of these methods and the challenges for transferring these methods into a practical and trustworthy framework for sufficient remote management of the patients.

/pdf/a-review-of-non-invasive-sensors-and-artificial-intelligence-353d8n0m.pdf

A review of non-invasive sensors and artificial intelligence models for diabetic foot monitoring

Infrared thermography (IRT) is a non-invasive tool to measure the body surface radiation temperature (Tsr). IRT is an upcoming technology as a result of recent advancements in camera lenses, detector technique and data processing capabilities. The purpose of this review is to determine the potential and applicability of IRT in the context of dynamic measurements in exercise physiology. We searched PubMed and Google Scholar to identify appropriate articles, and conducted six case experiments with a high-resolution IRT camera (640 × 480 pixels) for complementary illustration. Ten articles for endurance exercise, 12 articles for incremental exercise testing and 11 articles for resistance exercise were identified. Specific Tsr changes were detected for different exercise types. Close to physical exertion or during prolonged exercise six recent studies described “tree-shaped” or “hyper-thermal” surface radiation pattern (Psr) without further specification. For the first time, we describe the Tsr and Psr dynamics and how these may relate to physiological adaptations during exercise and illustrate the differential responsiveness of Psr to resistance or endurance exercise. We discuss how bias related to individual factors, such as skin blood flow, or related to environmental factors could be resolved by innovative technological approaches. We specify why IRT seems to be increasingly capable of differentiating physiological traits relevant for exercise physiologists from various forms of environmental, technical and individual bias. For refined analysis, it will be necessary to develop and implement standardized and accurate pattern recognition technology capable of differentiating exercise modalities to support the evaluation of thermographic data by means of radiomics.

Infrared Thermography in Exercise Physiology: The Dawning of Exercise Radiomics.

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Infrared Thermography in Exercise Physiology: The Dawning of Exercise Radiomics.