In recent years, non-contact infrared thermometers (NCITs) and infrared thermography (IRT) have gained prominence as convenient, non-invasive tools for human body temperature measurement. Despite their widespread adoption in a range of settings, there remain questions about their accuracy under varying conditions. This systematic review sought to critically evaluate the performance of NCITs and IRT in body temperature monitoring, synthesizing evidence from a total of 72 unique settings from 32 studies. The studies incorporated in our review ranged from climate-controlled room investigations to clinical applications. Our primary findings showed that NCITs and IRT can provide accurate and reliable body temperature measurements in specific settings and conditions. We revealed that while both NCITs and IRT displayed a consistent positive correlation with conventional, contact-based temperature measurement tools, NCITs demonstrated slightly superior accuracy over IRT. A total of 29 of 50 settings from NCIT studies and 4 of 22 settings from IRT studies achieved accuracy levels within a range of ±0.3 °C. Furthermore, we found that several factors influenced the performance of these devices. These included the measurement location, the type of sensor, the reference and tool, individual physiological attributes, and the surrounding environmental conditions. Our research underscores the critical need for further studies in this area to refine our understanding of these influential factors and to develop standardized guidelines for the use of NCITs and IRT.

Accurate body temperature measurement is essential for monitoring and managing safety during outdoor activities. Physical activities are an essential consideration for public health, with sports taking up an important proportion of these. Athletes’ performances can be directly affected by body temperature fluctuations, with overheating or hypothermia posing serious health risks. Monitoring these temperatures allows coaches and medical staff to make decisions that enhance performance and safety. Traditional methods, like oral, axillary, and tympanic readings, are widely used, but face challenges during intense physical activities in real-world environments. This study evaluated the agreement, correlation, and interchangeability of oral, axillary, and tympanic temperature measurements in outdoor exercise conditions. Systems developed for specific placements might generate different sensor readouts. Conducted as an observational field study, it involved 21 adult participants (11 males and 10 females, average age 25.14 ± 5.80 years) that underwent the Yo-Yo intermittent recovery test protocol on an outdoor court. The main outcomes measured were the agreement and correlation between temperature readings from the three methods, both before and after exercise. The results indicate poor agreement between the measurement sites, with significant deviations observed post-exercise. Although the Spearman correlation coefficients showed consistent temperature changes post-exercise across all methods, the standard deviations in the pairwise comparisons exceeded 0.67 °C. This study concluded that widely used temperature measurement methods are challenging to use during outdoor exercises and should not be considered interchangeable. This variability, especially after exercise, underscores the need for further research using gold standard temperature measurement methods to determine the most suitable site for accurate readings. Care should thus be taken when temperature screening is done at scale using traditional methods, as each measurement site should be considered within its own right.

Accurate estimation of core body temperature ($T_{c}$) is vital for monitoring thermoregulation and preventing heat-related illnesses under extreme environmental conditions. Invasive measurements are unsuitable for continuous use, motivating non-invasive computational alternatives. This study proposes a hybrid $T_{c}$ estimation method that integrates physiological signals, including heart rate ($HR$) and skin temperature ($T_{s}$), with environmental temperature ($T_{a}$) and humidity. The approach combines two differential equation-based thermoregulation models with a Random Forest regression model to improve predictive performance. Model parameters were jointly optimized, and performance was validated using leave-one-out cross-validation. The hybrid method achieved an RMSE of 0.24$~^\circ \mathrm{C}$ and a 95% limits of agreement of [-0.47$~^\circ \mathrm{C}$, 0.47$~^\circ \mathrm{C}$].

Objective. Accurate and non-invasive estimation of core body temperature (CBT) is essential for preventing heat-related illnesses during physical activity and thermal stress. The objective of this work is to develop and evaluate a framework for real-time CBT estimation using only heart rate (HR) data, enabling a lightweight solution suitable for deployment on wearable devices. Approach. We propose a multi-model Kalman filtering (KF) framework with variance-based fusion. Two variants were developed: a supervised Physiological State-Specific KF (PSSK) that uses activity labels (rest, exercise, recovery) to train distinct models, and an unsupervised trial clustering-based KF (TCBK) that clusters trials based on HR–CBT features to capture latent physiological variability without state annotations. Both models were evaluated on two independent datasets and compared against baseline methods. Main results. In within-dataset evaluations, TCBK achieved the highest accuracy with a root mean square error (RMSE) of 0.38 ∘ C (Dataset 1) and 0.41 ∘ C (Dataset 2). In cross-dataset generalization, PSSK demonstrated superior robustness with an RMSE of 0.88 ∘ C, whereas the TCBK model’s error increased to 1.56 ∘ C. Both proposed models outperformed the established Buller and Falcone models. Significance. This work demonstrates that lightweight, HR-only models can provide accurate CBT estimation by incorporating state- or context-aware modeling. The framework offers a practical and deployable solution for continuous thermal strain monitoring in occupational and athletic settings, providing a balance between performance and real-world applicability for wearable technology.