The use of thermal imaging in assessing skin temperature following cryotherapy : a review

Nineteen studies met the inclusion criteria. A skin temperature reduction of 5–15 °C, in accordance with the recent PRICE (Protection, Rest, Ice, Compression and Elevation) guidelines, were achieved using cold air, ice massage, crushed ice, cryotherapy cuffs, ice pack, and cold water immersion. There is evidence supporting the use and effectiveness of thermal imaging in order to access skin temperature following the application of cryotherapy. Thermal imaging is a safe and non-invasive method of collecting skin temperature. Although further research is required, in terms of structuring specific guidelines and protocols, thermal imaging appears to be an accurate and reliable method of collecting skin temperature data following cryotherapy. Currently there is ambiguity regarding the optimal skin temperature reductions in a medical or sporting setting. However, this review highlights the ability of several different modalities of cryotherapy to reduce skin temperature.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Use of thermal imaging in sports medicine research : a short report

The assessment of skin temperature (Tsk) in athletic therapy and sports medicine research is an extremely important physiological outcome measure.Various methodsof recording Tsk, including thermistors, thermocouples and thermocrons are currently being used for research purposes. These techniques are constrained by their wires limiting the freedom of the subject, slow response times, and/or sensors falling off. Furthermore, as these products typically are directly attached to the skin and cover the measurement site, their validity may be questionable.This manuscript addresses the use and potential benefits of using thermal imaging (TI) in sport medicine research.Non-contact infrared TI offers a quick, non-invasive, portable and athlete-friendly method of assessing Tsk. TI is a useful Tsk diagnostic tool that has potential to be an integral part of sport medicine research in the future. Furthermore, as the technique is non-contact it has several advantages over existing methods of recording skin temperature

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Infrared thermal imaging for automated detection of diabetic foot complications

Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Investigating limitations of SURF approach for thermal imaging analysis and mapping

Wildlife conservation involves an understanding of a specific animal, its environment and the interaction within a local ecosystem. Unmanned Aerial Vehicles (UAVs) present cost effective, non-intrusive solution for detecting animals over large areas and the use thermal imaging cameras offer the ability detect animals that would otherwise be concealed to visible light cameras. This report examines some of limitations on using SURF for the development of large maps using multiple stills images extracted from the thermal imaging video camera which contain wildlife (eg. Koala in them).

Analysis of the design-construction supply chain in the thermal performance of sub-tropical and tropical housing

Background: In sub-tropical and tropical Queensland, a legacy of poor housing design,minimal building regulations with few compliance measures, an absence of post-construction performance evaluation and various social and market factors has led to a high and growing penetration of, and reliance on, air conditioners to provide thermal comfort for occupants. The pervasive reliance on air conditioners has arguably impacted on building forms, changed cultural expectations of comfort and social practices for achieving comfort, and may have resulted in a loss of skills in designing and constructing high performance building envelopes. Aim: The aim of this paper is to report on initial outcomes of a project that sought to determine how the predicted building thermal performance of twenty-five houses in subtropical and tropical Queensland compared with objective performance measures and comfort performance as perceived by occupants. The purpose of the project was to shed light on the role of various supply chain agents in the realisation of thermal performance outcomes. Methodology: The case study methodology embraced a socio-technical approach incorporating building science and sociology. Building simulation was used to model thermal performance under controlled comfort assumptions and adaptive comfort conditions. Actual indoor climate conditions were measured by temperature and relative humidity sensors placed throughout each house, whilst occupants’ expectations of thermal comfort and their self-reported behaviours were gathered through semi-structured interviews and periodic comfort surveys. Thermal imaging and air infiltration tests, along with building design documents, were analysed to evaluate the influence of various supply chain agents on the actual performance outcomes. Results: The results clearly show that in the housing supply chain – from designer to constructor to occupant – there is limited understanding from each agent of their role in contributing to, or inhibiting, occupants’ comfort.

Multi-sensor tracking using a scalable condensation filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.

Multi-spectral fusion for surveillance systems

Surveillance systems such as object tracking and abandoned object detection systems typically rely on a single modality of colour video for their input. These systems work well in controlled conditions but often fail when low lighting, shadowing, smoke, dust or unstable backgrounds are present, or when the objects of interest are a similar colour to the background. Thermal images are not affected by lighting changes or shadowing, and are not overtly affected by smoke, dust or unstable backgrounds. However, thermal images lack colour information which makes distinguishing between different people or objects of interest within the same scene difficult. ----- By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using either modality individually. We evaluate four approaches for fusing visual and thermal images for use in a person tracking system (two early fusion methods, one mid fusion and one late fusion method), in order to determine the most appropriate method for fusing multiple modalities. We also evaluate two of these approaches for use in abandoned object detection, and propose an abandoned object detection routine that utilises multiple modalities. To aid in the tracking and fusion of the modalities we propose a modified condensation filter that can dynamically change the particle count and features used according to the needs of the system. ----- We compare tracking and abandoned object detection performance for the proposed fusion schemes and the visual and thermal domains on their own. Testing is conducted using the OTCBVS database to evaluate object tracking, and data captured in-house to evaluate the abandoned object detection. Our results show that significant improvement can be achieved, and that a middle fusion scheme is most effective.

Multi-modal object tracking using dynamic performance metrics

Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.

Project 2.7 Leveraging R&D Investment for the Australian built environment : Phase 2 Case Study Report Part 2 - Road Construction Safety

This report discusses findings of a case study into "Road Construction Safety" undertaken as a part of the retrospective analysis component of Sustainable Built Environment National Research Centre (SBEnrc) Project 2.7 Leveraging R&D investment for the Australian Built Environment. The Queensland Department of Transport and Main Roads (QTMR) has taken a leadership role in developing a safer working environment for road construction workers. In the past decades, a range of initiatives have been introduced to contribute to improved performance in this area. Several initiatives have been undertaken by QTMR as part of their overarching commitment to safety. Three such initiatives form the basis for this case study investigation, in order to better illustrate the nature of R&D investment and its impact on day-to-day operations and the supply chain. These are the development and implementation of: (i) the Mechanical Traffic Aid: (ii) the Thermal Imaging Camera; and (iii) the Trailer-based CCTV (camera). This case study should be read in conjunction with Part 1 of this suite of reports.

The effects of cold air (-110°C) and water (8°C) cryotherapy on knee skin temperature

Exposure to cold air, whole body cryotherapy (WBC), is a novel treatment employed by athletes. In WBC individuals dressed in minimal clothing are exposed to a temperature below -100°C for 2-4 min. The use of WBC has been advocated as a treatment for various knee injuries. PURPOSE: To compare the effects of two modalities of cryotherapy, -110°C WBC and 8°C cold water immersion (CWI) on knee skin temperature (Tsk). METHODS: With ethical approval and written informed consent 10 healthy active male participants (26.5±4.9 yr, 183.5±6.0 cm, 90.7±19.9 kg, 26.8±5.0 kg/m2, 23.0±9.3% body fat (measured by DXA), 7.6 ± 2.0 mm patellar skin fold; mean±SD) were exposed to 4 min of CWI and WBC. The treatment order was randomised in a controlled crossover design, with a minimum of 7 days between treatments. During WBC participants stood in a chamber (-60±3°C) for 20 s before entering the main chamber (-110°C±3°C) where they remained for 3 min and 40 s. For CWI participants were seated in a tank filled with cold water (8±0.3°C) and immersed to the level of the sternum for 4 min. Right knee Tsk was assessed via non-contact, infrared thermal imaging. A quadrilateral region of interest was created using inert markers placed 5 cm above and below the most superior and inferior aspect of the patella. Tsk within this quadrilateral was recorded pre, immediately post and every 10 min thereafter for 60 min. Tsk changes were examined using a two-way (treatment x time) repeated measures analyses of variance. In addition, a paired sample t-test was used to compare baseline Tsk before both treatments. RESULTS: Knee Tsk was similar before treatment (WBC: 29.9±0.7°C, CWI: 29.6±0.9°C, p>0.05). There was a significant main effect for treatment (p<0.05) and time (p<0.001). Compared to baseline, Tsk was significantly reduced (p<0.05) immediately post and at 10, 20, 30, 40, 50 and 60 min after both cooling modalities. Knee Tsk was lower (p<0.05) immediately after WBC (19.0±0.9°C) compared to CWI (20.5±0.6°C). However, from 10 to 60 min post, knee Tsk was lower (p<0.05) following the CWI treatment. CONCLUSION: WBC elicited a greater decrease in knee Tsk compared to CWI immediately after treatment. However, both modalities display different recovery patterns and Tsk after CWI was significantly lower than WBC at 10, 20, 30, 40, 50 and 60 min after treatment.

Effects of whole body cryotherapy and cold water immersion on knee skin temperature

This study sought to a) compare and contrast the effect of 2 commonly used cryotherapy treatments, 4 min of − 110 °C whole body cryotherapy and 8 °C cold water immersion, on knee skin temperature and b) establish whether either protocol was capable of achieving a skin temperature ( < 13 °C) believed to be required for analgesic purposes. After ethics committee approval and written informed consent was obtained, 10 healthy males (26.5 ± 4.9 yr, 183.5 ± 6.0 cm, 90.7 ± 19.9 kg, 26.8 ± 5.0 kg/m 2 , 23.0 ± 9.3 % body fat; mean ± SD) participated in this randomised controlled crossover study. Skin temperature around the patellar region was assessed in both knees via non-contact, infrared thermal imaging and recorded pre-, immediately post-treatment and every 10 min thereafter for 60 min. Compared to baseline, average, minimum and maximum skin temperatures were significantly reduced (p < 0.001) immediately post-treatment and at 10, 20, 30, 40, 50 and 60 min after both cooling modalities. Average and minimum skin temperatures were lower (p < 0.05) immediately after whole body cryotherapy (19.0 ± 0.9 ° C) compared to cold water immersion (20.5 ± 0.6 ° C). However, from 10 to 60 min post, the average, minimum and maximum skin temperatures were lower (p < 0.05) following the cold water treatment. Finally, neither protocol achieved a skin temperature believed to be required to elicit an analgesic effect.

Effect of moisture and temperature distribution on dried food microstructure and porosity

Dehydration of food materials requires water removal from it. This removal of moisture prevents the growth and reproduction of microorganisms that cause decay and minimizes many of the moisture-driven deterioration reactions (Brennan, 1994). However, during food drying, many other changes occur simultaneously resulting in a modified overall quality (Kompany et al., 1993). Among the physical attributes of dried food material porosity and microstructure are the important ones that can dominant other quality of dried foods (Aguilera et al., 2000). In addition, this two concerned quality attributes affected by process conditions, material components and raw structure of food stuff. In this work, temperature moisture distribution within food materials during microwave drying will be taken into consideration to observe its participation on the microstructure and porosity of the finished product. Apple is the selective materials for this work. Generally, most of the food materials are found in non-uniformed moisture contained condition. To develop non uniform temperature distribution, food materials have been dried in a microwave oven with different power levels (Chua et al., 2000). First of all, temperature and moisture model is simulated by COMSOL Multiphysics. Later on, digital imaging camera and Image Pro Premier software have been deployed to observation moisture distribution and thermal imaging camera for temperature distribution. Finally, Microstructure and porosity of the food materials are obtained from scanning electron microscope and porosity measuring devices respectively . Moisture distribution and temperature during drying influence the microstructure and porosity significantly. Specially, High temperature and moisture contained regions show less porosity and more rupture. These findings support other literatures of Halder et al. (2011) and Rahman et al (1990). On the other hand, low temperature and moisture regions depict uniform microstructure and high porosity. This work therefore assists in better understanding of the role of moisture and temperature distribution to a prediction of micro structure and porosity of dried food materials.