The effect of work related mechanical stress on the peripheral temperature of the hand

The evolution and developments in modern industry have resulted a wide range of occupational activities, some of which can lead to industrial injuries. Due to the activities of occupational medicine, much progress has been made in transforming the way that operatives perform their tasks. However there are still many occupations where manual tasks have become more repetitive, contributing to the development of conditions that affect the upper limbs. Repetitive Strain Injury is one classification of those conditions which is related to overuse of repetitive movement. Hand Arm Vibration Syndrome is a subtype of this classification directly related to the operation of instruments and machinery which involves vibration. These conditions affect a large number of individuals, and are costly in terms of work absence, loss of income and compensation. While such conditions can be difficult to avoid, they can be monitored and controlled, with prevention usually the least expensive solution. In medico-legal situations it may be difficult to determine the location or the degree of injury, and therefore determining the relevant compensation due is complicated by the absence of objective and quantifiable methods. This research is an investigation into the development of an objective, quantitative and reproducible diagnostic procedure for work related upper limb disorders. A set of objective mechanical provocation tests for the hands have been developed that are associated with vascular challenge. Infrared thermal imaging was used to monitor the temperature changes using a well defined capture protocol. Normal reference values have been measured and a computational tool used to facilitate the process and standardise image processing. These objective tests have demonstrated good discrimination between groups of healthy controls and subjects with work related injuries but not individuals, p<0.05, and are reproducible. A maximum value for thermal symmetry of 0.5±0.3ºC for the whole upper limbs has been established for use as a reference. The tests can be used to monitor occupations at risk, aiming to reduce the impact of these conditions, reducing work related injury costs, and providing early detection. In a medico-legal setting this can also provide important objective information in proof of injury and ultimately in objectively establishing whether or not there is a case for compensation

Comparison of machine learning strategies for infrared thermography of skin cancer

Objective: The aim of this work was to explore the potential of infrared thermal imaging as an aiding tool for the diagnosis of skin cancer lesions, using artificial intelligence methods. Methods: Thermal parameters of skin tumours were retrieved from thermograms and used as input features for two machine learning based strategies: ensemble learning and deep learning. Results: The deep learning strategy outperformed the ensemble learning one, showing good predictive performance for the differentiation of melanoma and nevi (Precision=0.9665, Recall=0.9411, f1-score=0.9536, ROC(AUC)=0.9185) and melanoma and non-melanoma skin cancer (Precision=0.9259, Recall=0.8852, f1-score=0.9051, ROC(AUC)=0.901). Conclusion: IRT imaging combined with deep learning techniques is promising for simplifying and accelerating the diagnosis of skin cancer. Significance: Despite ongoing awareness campaigns for skin cancer’ risk factors, its incidence rate has continuously been growing worldwide, becoming a major public health issue. The standard first detection method – dermoscopy –, is largely experience-dependent and mostly used to assess melanocytic lesions. As infrared thermal imaging is an innocuous imaging technique that maps skin surface temperature, which may be associated to pathological states, e.g., tumorous lesions, it could be a potential aiding tool for all skin cancer conditions. The application of artificial intelligence methods to process the collected temperature data can save time and assist health care professionals with low experience levels in the diagnosis task. To the best of our knowledge, this is the first study where a data set of skin cancer thermograms is expanded and used for skin lesion differentiation with a deep learning approach.info:eu-repo/semantics/publishedVersio

A proposal of a standard rainbow false color scale for thermal medical images

Medical thermal imaging offers the opportunity of human body physiology monitoring. The frequent use of false color scales in those images has the objective of being a visual aid for human eye interpretation. However, several scales are being used, which may lead to different subjective interpretations. Is objective of this study to raise the need of uniformity in adoption of an internationally accepted standard false color scale and for that purpose a scale is proposed.info:eu-repo/semantics/publishedVersio

A case study on dynamic thermal imaging evaluation of a thyroid nodule

BACKGROUND:The thyroid gland is a butterfly-shaped organ located in the neck anteriorly to the larynx and trachea, typically extending from the level of C5-T1. It is responsible for the release of hormones that control metabolic rates and thereby modifying obligatory and adaptive thermogenesis. This organ can be affected by nodules and cellular malforma- tions, which can result in malignant neoplasia or benign cysts. Those manifestations may change the normal pattern of skin temperature distribution in the affected area. The aim of this study is to investigate the thermal pattern of a subject presenting a hypervascularized nodule located on the left side of the thyroid. MATERIALS AND METHODS: A male with 40 years old presenting a 11x6 mm nodule in the left side of his thyroid, con- firmed by functional doppler imaging, was examined in a controlled environment using a FLIR E60 thermal camera and two aluminium disks to provide a cooling provocation during one minute on the skin, above the thyroid gland location. Thermal images were taken before and until the fifth minute after cooling at an interval of 1 minute. A 26x26 pixel square region of interest (ROI) was drawn in the analysis software to statistically analyze the temperature values, histogram, mean, median and mode temperature, standard deviation, kurtosis and skewness per ROI and side. RESULTS:The ROI presented at baseline a bilateral difference in mean temperature of 0.4 ºC, after cooling this difference was accentuated, the affected side recovered quickly and showed a hot spot in the area of the nodule identified by Doppler imaging. CONCLUSION:This case study showed evidence of the utility on using dynamic infrared thermal imaging when assess ing thyroid nodules, which was confirmed by Doppler imaging to be highly vascularized. However, for diagnostic pur poses the traditional expensive methods such as biopsy and nuclear medicine are still required. Still the application of IRT imaging should be further researched in possible monitoring and documenting the diagnosis and treatment evaluation applied to thyroid conditions.info:eu-repo/semantics/publishedVersio

Meta-Analysis and Systematic Review of the Application of Machine Learning Classifiers in Biomedical Applications of Infrared Thermography

Atypical body temperature values can be an indication of abnormal physiological processes associated with several health conditions. Infrared thermal (IRT) imaging is an innocuous imaging modality capable of capturing the natural thermal radiation emitted by the skin surface, which is connected to physiology-related pathological states. The implementation of artificial intelligence (AI) methods for interpretation of thermal data can be an interesting solution to supply a second opinion to physicians in a diagnostic/therapeutic assessment scenario. The aim of this work was to perform a systematic review and meta-analysis concerning different biomedical thermal applications in conjunction with machine learning strategies. The bibliographic search yielded 68 records for a qualitative synthesis and 34 for quantitative analysis. The results show potential for the implementation of IRT imaging with AI, but more work is needed to retrieve significant features and improve classification metrics.info:eu-repo/semantics/publishedVersio

Skin temperature of the foot: Reliability of infrared image analysis based in the angiosome concept

Objective: Studies reporting the reliability of image analysis when assessing skin temperature of the foot are scarce. The aim of this study was to assess the interrater and intrarater reliability of the analysis of foot skin temperature based on the angiosome concept and the association between skin temperature differences and the differences in size of the ROIs. Methodology: Thermograms from 26 feet were analysed by two independent assessors and each assessor analysed the same images on different occasions. Mean temperature values of each of the six ROIs were extracted for analysis. Relative reliability was assessed by Intraclass Correlation Coefficient (ICC) measures and absolute reliability was assessed using Bland and Altman agreement measures and standard error of measurement (SEM). The Spearman correlation coefficient was used to assess the association between the skin temperature differences and the differences in size of the ROIs in the interrater and intrarater analysis Results: The ICC values evidenced excellent interrater and intrarater reliability with the 95% confidence intervals (CI) ranging between 0.962 and 1.000 and the SEM ranged between 0.00 °C and 0.36 °C. The mean absolute difference (bias) between the measurements ranged between 0.002 °C and 0.117 °C and small to moderate associations between the differences in skin temperature and the difference in the number of pixels were identified.Conclusion: The excellent interrater and intrarater reliability measures suggest that the methodology of analysis was reliable and may be used in research and clinical settings. Although statistical significant associations between the skin temperature differences and the differences in size of the ROIs were found, the magnitude of the skin temperature differences between assessments and between assessors (0.02–0.17 °C) is not clinically relevant.info:eu-repo/semantics/publishedVersio

Building Low Cost Cloud Computing Systems

The actual models of cloud computing are based in megalomaniac hardware solutions, being its implementation and maintenance unaffordable to the majority of service providers. The use of jail services is an alternative to current models of cloud computing based on virtualization. Models based in utilization of jail environments instead of the used virtualization systems will provide huge gains in terms of optimization of hardware resources at computation level and in terms of storage and energy consumption. In this paper it will be addressed the practical implementation of jail environments in real scenarios, which allows the visualization of areas where its application will be relevant and will make inevitable the redefinition of the models that are currently defined for cloud computing. In addition it will bring new opportunities in the development of support features for jail environments in the majority of operating systems.info:eu-repo/semantics/publishedVersio

Bilateral assessment of body core temperature through axillar, tympanic and inner canthi thermometers in a young population

There are several sites in which the human body core temperature can be estimated and used to identify febrile states in a threat of pandemic situations at high-populational-traffic places (e.g. airports, ports, universities, schools, public buildings). In these locations, a fast method is required for temperature screening of masses. The most common methods are axillar and tympanic thermometers. However, in addition, measurement of the inner canthi (IC) of the eye with infrared thermal (IRT) imaging has been suggested as a fast mass measurement screening tool. Objective: It is the aim of this research to identify the bilateral difference of the available body temperature screening methods with potential use for large-scale fever screening and to verify if such a difference is acceptable. Approach: A total of 206 young participants (104 females and 102 males) were recruited, having their temperatures taken with the different methods bilaterally under neutral environmental conditions. The obtained results were statistically processed. Main results: Results established absent reference data for site and method in west European populations. The bilateral differences were minor using the IC of the eye monitored with infrared imaging, which was also proved with the Bland–Altmann limits of agreement. Significance: Based on the findings of this research, despite all methods being able to estimate body core temperature, it is suggested to use IRT images of the IC of the eye, due to its fast, reliable and reproducible procedure for mass screening. Further research is required to understand the higher bilateral variability in using the traditional thermometer axilla and tympanic membrane assessments, since these are the methods currently used within a clinical setup. The same procedure must be applied to fever cases to establish a decision threshold per method.info:eu-repo/semantics/publishedVersio

IMAGE ANALYSIS AND MACHINE LEARNING CLASSIFICATION FOR SKIN CANCER THERMAL IMAGES USING OPEN SOURCE TOOLS

The incidence of skin cancer cases is constantly growing, causing a great burden in health care systems. The interest in using infrared thermal (IRT) imaging to assess atypical skin temperature values associated with skin lesions has grown, as it allows an innocuous and fast evaluation. The processing, collection, and integration of IRT parameters is a challenging task, becoming a tendency to adopt ma chine learning (ML) strategies. Still, there is not a great number of published research focused on the conception of applications or platforms to perform these tasks. The main aim of this work is the conception and development of two open-source interfaces, using Python programming language, to facilitate and assist in the performance of skin cancer thermograms' image analysis and classification.info:eu-repo/semantics/publishedVersio

Recent use of medical infrared thermography in skin neoplasms

Background: Infrared thermal imaging captures the infrared radiation emitted by the skin surface. The thermograms contain valuable information, since the temperature distribution can be used to characterize physiological anomalies. Thus, the use of infrared thermal imaging (IRT) has been studied as a possible medical tool to aid in the diagnosis of skin oncological lesions. The aim of this review is to assess the current state of the applications of IRT in skin neoplasm identification and characterization. Methods: A literature survey was conducted using the reference bibliographic databases: Scopus, PubMed and ISI Web of Science. Keywords (thermography, infrared imaging, thermal imaging and skin cancer) were combined and its presence was verified at the title and abstract of the article or as a main topic. Only articles published after 2013 were considered during this search. Results: In total, 55 articles were encountered, resulting in 14 publications for revision after applying the exclusion criteria. It was denoted that IRT have been used to characterize and distinguish between malignant and benign neoplasms and different skin cancer types. IRT has also been successfully applied in the treatment evaluation of these types of lesions. Conclusion: Trends and future challenges have been established to improve the application of IRT in this field, disclosing that dynamic thermography is a promising tool for early identification of oncological skin conditions.info:eu-repo/semantics/publishedVersio