Springer Science and Business Media LLC

Infrared thermography has been used in many medical applications. Objective: The objective of this study was to investigate, through systematic review and meta-analysis, studies using medical thermography for the diagnosis fractures and clinical follow-up of bone healing. Methods: Articles were selected from SciELO, MEDLINE/PubMed, Lilacs, Google Scholar, and Science Direct databases, between the years 2000 to 2020, using the descriptors: medical image/clinical diagnosis/bone fracture/bone consolidation/thermographic analysis identified by the Health Sciences and Medical Subject Headings, in English, Portuguese, and Spanish. The results of the studies were combined through the fixed effects model using the Mantel–Haenszel method and random effects analysis using the DerSimonian–Laird method. The quality of the studies was evaluated using the QUADAS-2 scale and the level of evidence, by the GRADE system, regarding the effectiveness of infrared thermography in diagnosing bone fractures. Results: of 364 articles identified, 12 studies were selected for quantitative analysis. The meta-analysis showed a sensitivity of up to 97.5% and specificity of 98.8% in detecting bone injuries. Conclusions: The evaluation of bone fractures by infrared medical thermography has demonstrated high sensitivity, reliability, and efficacy as a complementary method for monitoring. Thus, it can minimize the use of ionizing radiation-based examinations such as X-rays.

The work of railway gangmen is physically demanding and challenging one. They have to undergo a routine walk of 8–12 km carrying a bag with all the tools which weighs 18 kg to inspect the track for the maintenance. Chances of work-related musculoskeletal disorders (WMSD) are high among the railway workers. The body part at which they feel more pain during their works can be founded out from the biomechanical analysis. Biomechanical analysis of the gangmen during the loaded walking and key man hammering has been carried out using OpenSim software and pointed out the most affected body part at which they feel more pain and WMSD. Further field survey was conducted among the railway gangmen of Palakkad Junction railway station, Kerala, India and further WMSD pain was modelled using binary logistic regression with age, weight, path covered during work and experience as explanatory variables. Peak value of flexion moment at hip, extension moment at lumbar, and bending moment at lumbar has the larger value of 232.41, 231.47, and 124.94 Nm, respectively, which points the reason for the back pain during the loaded walking. Similarly, peak value of elevation moment at shoulder and rotation moment at shoulder are 107.5 and 15.23 Nm, respectively, also indicated that shoulder as the most affected part of the keyman leading to WMSD. From the statistical analysis of the survey, it can be observed that age 1.21 (1.03–1.48); 1.30 (1.07–1.67) and weight 1.25 (1.10–1.66); 1.30 (1.07–1.68) are significant at p < .05 in influencing WMSD pain in leg and shoulders of railway workers. Highest moments are acting on the hip, lumbar joints, and pelvis while loaded walking whereas on the shoulder during keyman hammering. The age and weight of the gangmen significantly influences pain experiences on leg and shoulder. This method can be used for the early detection of risk involved in the occupational biomechanics of railway gangmen which may lead to WMSD.

Lung cancer is the second most common type of cancer prevalent in men worldwide. The early diagnosis of lung cancer can reduce cancer-related deaths considerably and increase the survival rate for a few years. In recent years, computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems emerged as promising techniques for radiologists for the early diagnosis of lung cancer. An efficient pre-processing technique and accurate segmentation of the lung parenchyma in medical images will reduce false positives, which in turn can considerably improve the specificity of classification of the lung nodules as benign or malignant. A novel framework for preprocessing lung images and segmentation of the region of interest is proposed in this study. The noise removal in low-dose computed tomography (LDCT) images is performed by discrete wavelet transform with adaptive thresholding (DWTWAT). The segmentation of the lung region is performed by genetic algorithm enhanced K-means clustering (GAK-means) and genetic algorithm enhanced Fuzzy c-means clustering (GAFCM) in LDCT images. The segmentation is followed by lung reconstruction to preserve the juxta-pleural and Pleural tail nodules attached to the lung boundary. The proposed methods were individually evaluated with the commonly used metrics of sensitivity, specificity, and accuracy. The novel noise removal technique of DWTWAT and segmentation with GAFCM has achieved a sensitivity, specificity, and accuracy of 99.54%, 99.99%, and 99.54%, respectively. The noise removal technique of DWTWAT for preprocessing and segmentation with GAK-means has achieved sensitivity, specificity, and accuracy of 99.47%, 99.77%, and 99.26%. The proposed techniques of noise removal and segmentation is a novel combination that showed improved results compared to the existing state-of-the-art method.

Medical infrared thermography (IRT) was used as a complementary means for the clinical evaluation of musculoskeletal trauma and progression of chronic tibial osteomyelitis. Twenty-two adult patients with a medical diagnosis of chronic tibial osteomyelitis were followed up by IRT performed along with standard radiography. Thermal data of the affected limb were compared with those of the healthy contralateral limb based on the thermal profile of the lower limbs as per the medical thermography guideline (32 °C). Data were acquired in the following regions of the lower limb: proximal tibia, diaphysis, and distal tibia, using a FLIR infrared camera, and data were processed using MATLAB®. For patients with active infections, an increase in the average temperature of the affected limb above + 1.0 °C was observed when compared with the temperature of the contralateral. The wound region of the patients showed an increased temperature (32.3 °C) compared with the temperature of the contralateral (31.4 °C). In contrast, in latent infections, the thermal differences were small, generally below 0.3 °C, and thus were within the threshold of normality. In contrast, in areas diagnosed with reduced blood supply, the affected limb showed an average temperature up to − 5.7 °C below normal. Additionally, the initial temperature range (26.5 to 34.5 °C) decreased during the treatment to 29.8 to 34.1 °C, indicating a convergence toward normality. IRT has significant potential as a complementary imaging modality in the follow-up of patients with bone lesions with a diagnosis of osteomyelitis as it does not use ionizing radiation, thus allowing repetitive use as desired. Thermal images show important physiological information related to vascularization necessary for bone repair, as well as provide a good indication of the boundary of the infected area, adjacent to the trauma, which is useful for positioning the radiography equipment. However, it should be noted that IRT cannot replace other medical imaging techniques, as it provides information about the skin and cannot directly evaluate the interior of the body.

Lung diseases are the top causes of death around the world nowadays. Chest X-rays (CXRs) provide an invaluable tool for diagnosing lung-related diseases at the earliest stage possible. However, the accuracy of the diagnosis results depends heavily on the skill of the radiologist and is inevitably time-consuming and subjective. Accordingly, the present study proposes a model-based learning approach for the automatic detection of thoracic disease from CXR images designated as Segmentation-Guided Thorax Classification (SGTC). The proposed method consists of two stages, namely lung segmentation and thorax classification. The lung segmentation stage applies the U-Net model with ResNet-50 as the backbone to segment the lung region in the CXR. The thorax classification stage then utilizes the ChexNet model with DenseNet-121 as the backbone to evaluate the probability of 14 different thoracic pathologies. The experimental results show that SGTC achieves an average area under the receiver operating characteristic (ROC) curve (AUC) of 0.844 when applied to the ChestX-ray14 dataset. The performance of the proposed method is comparable to that of other recent approaches. Moreover, SGTC additionally superimposes a localization heatmap on the CXR image, which further assists the radiologist in interpreting the image.

Rising from a sitting position, or “sit-to-stand” (STS), is one of the basic activities in daily life. Therefore, studying the kinematics and kinetics of STS could help optimize STS movement strategy. This study analyzes the comprehensive influence of the handrail and foot position under the knee joint support on STS kinematics and kinetics. A total of 30 young people were recruited to participate in this study. Their average age, height, weight, and BIM were 24.21 years old, 168.52 cm, 60.92 kg, and 21.46 kg/m2, respectively. The experiment was conducted under six experimental conditions. Total movement time, percent of movement time of each phase, trunk tilt angle, and peak joint moment were analyzed and compared. In addition, a correlation analysis was carried out between the range of motion of the joint angle and the peak joint moment. The results showed that the far handrail had the largest trunk tilt angle, and the smallest total moment impulse of the lower limb joints. The closer the foot was to the seat, the smaller the peak hip joint moment, and the larger the peak moment of ankle and knee joints, and a shorter total movement time. The position of the handrail had a significant influence on the trunk tilt angle, percent of movement time of certain phase, and the total moment impulse of the lower limb joints. And the position of the foot had a significant influence on the peak moments of the ankle, hip, and knee joints.

Cup-feeding is an alternative method for newborn feeding. Although there are cups in use for this purpose, there are still some concerns about their adequacy. The objective was to develop a cup considering the physiology of the oromotor function and the stages of sucking development. To develop this cup, it was considered the newborn mouth’s anatomy (term and preterm), their oromotor functions, and the maturation levels of the oromotor functions, the milk flow velocity, and the newborn’s ability to deal with the milk volumes reaching their mouth. Also this device had to be safe to be used in nurseries and neonatal units, so it needed to be adequate for the transportation of human milk from the human milk bank to the unit. It contains a metering nipple, a flow reducer, a scale to inform the milk volume being offered, and a cover. A safety study in 22 term and 22 preterm newborns was performed. The diameter of the metering nipple was adequate to both term and preterm newborns, without risks to the integrity of their lips and tongue. The flow reducer allowed a better control of the milk volume, contributing for the organization of the swallowing, with less spillage of milk. There were no discomfort during the proceedings. This cup showed that it is a good and safe feeding device for term and preterm newborns in the transition to breastfeeding. This cup is safe to be used in Neonatal Intensive Care Units or Nurseries.