Infrared thermography can detect previsual bacterial growth in a laboratory setting via metabolic heat detection.

AIMS: Detection of bacterial contamination in healthcare and industry takes many hours if not days. Thermal imaging, the measurement of heat by an infrared camera, was investigated as a potential noninvasive method of detecting bacterial growth. METHODS AND RESULTS: Infrared thermography can detect the presence of Escherichia coli and Staphylococcus aureus on solid growth media by an increase in temperature before they are visually observable. A heat decrease is observed after treatment with ultraviolet light and heat increased after incubation with dinitrophenol. CONCLUSIONS: Infrared thermography can detect early growth of bacteria before they are detectable by other microbiology-based method. The heat observed is due to the cells being viable and metabolically active, as cells killed with ultraviolet light exhibit reduced increase in temperature and treatment with dinitrophenol increases heat detected. SIGNIFICANCE AND IMPACT OF THE STUDY: Infrared thermography detects bacterial growth without the need for specialized temperature control facilities. The method is statistically robust and can be undertaken in situ, thus is highly versatile. These data support the application of infrared thermography in a laboratory, clinical and industrial setting for vegetative bacteria, thus may become into an important methodology for the timely and straightforward detection of early-stage bacterial growth.

Building artificial intelligence and machine learning models : a primer for emergency physicians.

There has been a rise in the number of studies relating to the role of artificial intelligence (AI) in healthcare. Its potential in Emergency Medicine (EM) has been explored in recent years with operational, predictive, diagnostic and prognostic emergency department (ED) implementations being developed. For EM researchers building models de novo, collaborative working with data scientists is invaluable throughout the process. Synergism and understanding between domain (EM) and data experts increases the likelihood of realising a successful real-world model. Our linked manuscript provided a conceptual framework (including a glossary of AI terms) to support clinicians in interpreting AI research. The aim of this paper is to supplement that framework by exploring the key issues for clinicians and researchers to consider in the process of developing an AI model.

Exploratory Study to Evaluate Respiratory Rate Using a Thermal Imaging Camera.

BACKGROUND: Respiratory rate is a vital physiological measurement used in the immediate assessment of unwell children and adults. Convenient electronic devices exist for the measurement of pulse, blood pressure, oxygen saturation, and temperature. Although devices which measure respiratory rate exist, none have entered everyday clinical practice for acute assessment of children and adults. An accurate and practical device which has no physical contact with the patient is important to ensure readings are not affected by distress caused by the assessment method. OBJECTIVE: The aim of this study was to evaluate the use of a thermal imaging method to monitor the respiratory rate in children and adults. METHODS: Facial thermal images of adult volunteers and children undergoing elective polysomnography were included. Respiration was recorded for at least 2 min with the camera positioned 1 m from the subject's face. Values obtained using the thermal imaging camera were compared with those obtained from contact methods such as the nasal thermistor, respiratory inductance plethysmography, nasal airflow, and end tidal CO2. RESULTS: A total of 61 subjects, including 41 adults (age range 27-46 years) and 20 children (age range 0.5-18 years) were enrolled. The correlation between the respiratory rate measured using thermal imaging and the contact method was r = 0.94. Sequential refinements to the thermal imaging algorithms resulted in the ability to perform real-time measurements and an improvement of the correlation to r = 0.995. CONCLUSION: This exploratory study shows that thermal imaging-derived respiratory rates in children and adults correlate closely with the best performing standard method. With further refinements, this method could be implemented in both acute and chronic care in children and adults.

Convolutional Neural Network to Classify Infrared Thermal Images of Fractured Wrists in Pediatrics.

Convolutional neural network (CNN) models were devised and evaluated to classify infrared thermal (IRT) images of pediatric wrist fractures. The images were recorded from 19 participants with a wrist fracture and 21 without a fracture (sprain). The injury diagnosis was by X-ray radiography. For each participant, 299 IRT images of their wrists were recorded. These generated 11,960 images (40 participants × 299 images). For each image, the wrist region of interest (ROI) was selected and fast Fourier transformed (FFT) to obtain a magnitude frequency spectrum. The spectrum was resized to 100 × 100 pixels from its center as this region represented the main frequency components. Image augmentations of rotation, translation and shearing were applied to the 11,960 magnitude frequency spectra to assist with the CNN generalization during training. The CNN had 34 layers associated with convolution, batch normalization, rectified linear unit, maximum pooling and SoftMax and classification. The ratio of images for the training and test was 70:30, respectively. The effects of augmentation and dropout on CNN performance were explored. Wrist fracture identification sensitivity and accuracy of 88% and 76%, respectively, were achieved. The CNN model was able to identify wrist fractures; however, a larger sample size would improve accuracy.

Kohonen Neural Network Investigation of the Effects of the Visual, Proprioceptive and Vestibular Systems to Balance in Young Healthy Adult Subjects.

Kohonen neural network (KNN) was used to investigate the effects of the visual, proprioceptive and vestibular systems using the sway information in the mediolateral (ML) and anterior-posterior (AP) directions, obtained from an inertial measurement unit, placed at the lower backs of 23 healthy adult subjects (10 males, 13 females, mean (standard deviation) age: 24.5 (4.0) years, height: 173.6 (6.8) centimeter, weight: 72.7 (9.9) kg). The measurements were based on the modified Clinical Test of Sensory Interaction and Balance (mCTSIB). KNN clustered the subjects' time-domain sway measures by processing their sway's root mean square position, velocity, and acceleration. Clustering effectiveness was established using external performance indicators such as purity, precision-recall, and F-measure. Differences in these measures, from the clustering of each mCTSIB condition with its condition, were used to extract information about the balance-related sensory systems, where smaller values indicated reduced sway differences. The results for the parameters of purity, precision, recall, and F-measure were higher in the AP direction as compared to the ML direction by 7.12%, 11.64%, 7.12%, and 9.50% respectively, with their differences statistically significant (p < 0.05) thus suggesting the related sensory systems affect majorly the AP direction sway as compared to the ML direction sway. Sway differences in the ML direction were lowest in the presence of the visual system. It was concluded that the effect of the visual system on the balance can be examined mostly by the ML sway while the proprioceptive and vestibular systems can be examined mostly by the AP direction sway.

Juvenile Idiopathic Arthritis: A Review of Novel Diagnostic and Monitoring Technologies.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease of childhood and is characterized by an often insidious onset and a chronic relapsing-remitting course, once diagnosed. With successive flares of joint inflammation, joint damage accrues, often associated with pain and functional disability. The progressive nature and potential for chronic damage and disability caused by JIA emphasizes the critical need for a prompt and accurate diagnosis. This article provides a review of recent studies related to diagnosis, monitoring and management of JIA and outlines recent novel tools and techniques (infrared thermal imaging, three-dimensional imaging, accelerometry, artificial neural networks and fuzzy logic) which have demonstrated potential value in assessment and monitoring of JIA. The emergence of novel techniques to assist clinicians' assessments for diagnosis and monitoring of JIA has demonstrated promise; however, further research is required to confirm their clinical utility.

Traumatic brain injury probability of survival assessment in adults using iterative random comparison classification.

Trauma brain injury (TBI) is the most common cause of death and disability in young adults. A method to determine the probability of survival (Ps) in trauma called iterative random comparison classification (IRCC) was developed and its performance was evaluated in TBI. IRCC operates by iteratively comparing the test case with randomly chosen subgroups of cases from a database of known outcomes (survivors and not survivors) and determines the overall percentage match. The performance of IRCC to determine Ps in TBI was compared with two existing methods. One was Ps14 that uses regression and the other was predictive statistical diagnosis (PSD) that is based on Bayesian statistic. The TBI database contained 4124 adult cases (mean age 67.9 years, standard deviation 21.6) of which 3553 (86.2%) were survivors and 571 (13.8%) were not survivors. IRCC determined Ps for the survivors and not survivors with an accuracy of 79.0 and 71.4%, respectively, while the corresponding values for Ps14 were 97.4% (survivors) and 40.2% (not survivors) and for PSD were 90.8% (survivors) and 50% (not survivors). IRCC could be valuable for determining Ps in TBI and with a suitable database in other traumas.

Infrared thermal imaging as a screening tool for paediatric wrist fractures.

Wrist injuries are common in paediatric trauma; however, only half of children evaluated with an x-ray for possible fractures will have one. Thermal imaging offers a possible non-ionising method of screening for fractures and thus reducing negative x-ray rates. One hundred five children attending the Emergency Department for wrist injuries were recruited. Two 30-s thermal videos were recorded from injured and uninjured wrists-in flat and 45° elevated positions. A region of interest (ROI) was defined on each wrist. Cases in which the ROI was covered or had ice applied were excluded, leaving 40 patients for analysis. Comparisons of ROI included (i) injured and uninjured wrists-flat and elevated positions; (ii) as in (i) with a reference region on the proximal forearm subtracted; (iii) injured wrist ROI-flat and elevated positions. Fractures and sprains increased the mean skin surface temperature by 1.519% (p = 0.008) and 0.971% (p = 0.055) respectively compared with the uninjured wrist. The mean temperature difference between flat and elevated positions for fractures was 0.268% and - 0.1291% for sprains. This difference was statistically significant for fracture (p = 0.004) but not sprain (p = 0.500). The temperature differences recorded by thermal imaging between fractured and sprained wrists may assist in differentiation of these injuries. Graphical abstract Operational stages involved from thermal video recording to generation of results.

Evaluation of high resolution thermal imaging to determine the effect of vertebral fractures on associated skin surface temperature in children with osteogenesis imperfecta.

Vertebral fractures are common in children with osteogenesis imperfecta (OI). Current imaging methods for fracture detection (X-ray and DXA) use ionising radiation. This pilot study explored whether the alteration in blood flow in vertebral fractures results in skin temperature changes that may be detected using high resolution thermal imaging (HRTI) and thus assist diagnosis and monitoring of fractures in OI patients. Eleven participants aged 5-18 years with OI and known vertebral fractures were enrolled. Small metal discs were placed on the skin surface alongside the vertebrae before participants had DXA and X-ray scans and thermal imaging of their backs. Visibility of the discs on the DXA and X-ray scans and thermal images allowed the temperatures of the skin surface above vertebrae without (healthy) and with fractures to be compared to their respective adjacent skin surface regions (region of reference, ROR) by calculating the temperature percentage change (TPC). The TPC between the skin temperature over the fractured thoracic vertebrae (n = 11) and the ROR was significant (1.44%, p = 0.002, 95% confidence). TPC between the skin temperature over healthy thoracic vertebrae and ROR was not significant (0.97%, p = 0.15, 95% confidence). HRTI may provide a novel tool for assisting in detection of vertebral fractures in OI. Graphical abstract • Patients (aged 5-18) with osteogenesis imperfecta and known vertebral fractures. • Thermal imaging was performed alongside routine imaging (DXA scan and spinal X-ray). • The temperature above each vertebra was compared with its adjacent skin region to assist with diagnosis of the fracture.

Adaptive Sampling Technique Using Regression Modelling and Fuzzy Inference System for Network Traffic.

Electronic-health relies on extensive computer networks to facilitate access and to communicate various types of information in the form of data packets. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of packets, examining their transmission parameters individually is not practical, especially when performed in real time. Sampling allows a subset of packets that accurately represents the original traffic to be chosen. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the sampling by responding to the traffic changes. Its performance was found to be superior to the conventional non-adaptive sampling methods.

Inertial Measurement Techniques for Human Joints' Movement Analysis.

Development and assessment of techniques that allow inertia measurement units consisting of an accelerometer and a gyroscope to be used for monitoring human joints' movements are presented. A new wavelet packet decomposition technique was developed that denoised the accelerometer signals. Investigations on the use of accelerometers to analyse legs' movements are described.

Fuzzy Logic to Determine the Likelihood of Survival for Trauma Injury Patients.

A system to determine the likelihood of survival for trauma injury patients is being developed. It uses a fuzzy logic approach that can model complex processes without reliance on sophisticated mathematical formulations and may have the potential to be more accurate than the existing approaches. The outline operation of the system that is currently in a prototype stage is described.

The effects of ageing on stereopsis. A VEP study.

Differences in brain activation between young (n = 11, ages 21-35) and elderly (n = 8, ages 70-84) healthy participants were studied using visual evoked potentials (VEPs) to different kinds of computer generated random-dot patterns. The main stimulus of interest was a 2 x 2 array of rectangles whose rectangles moved to and fro in depth. Control conditions were similar 2 x 2 arrays, one with side-to-side lateral motion (LM) of the rectangles, and one a stationary baseline condition. The third non-stereo stimulus was an expanding field of small dots in radial motion (RM). Significant stereo related activation was found in both age groups. The stereo VEPs showed a longer latency of depth reversal triggered VEP peaks compared to control LM VEPs. The amplitudes of LM VEPs were larger than the baseline VEPs. Age-related differences were found not only in stereo but also in the other conditions. Thus the latency of early VEP peaks was shorter and their amplitude higher in the elderly for LM and baseline conditions, and the younger participants showed significantly higher activation in the later VEP peaks of all conditions. Our main finding is no evidence for age related stereo specific effects in brain activation, but instead more general and subtle changes that affect widely different visual stimulus conditions.