Deep Learning-Based Fish Detection Using Above-Water Infrared Camera for Deep-Sea Aquaculture: A Comparison Study.

Long-term, automated fish detection provides invaluable data for deep-sea aquaculture, which is crucial for safe and efficient seawater aquafarming. In this paper, we used an infrared camera installed on a deep-sea truss-structure net cage to collect fish images, which were subsequently labeled to establish a fish dataset. Comparison experiments with our dataset based on Faster R-CNN as the basic objection detection framework were conducted to explore how different backbone networks and network improvement modules influenced fish detection performances. Furthermore, we also experimented with the effects of different learning rates, feature extraction layers, and data augmentation strategies. Our results showed that Faster R-CNN with the EfficientNetB0 backbone and FPN module was the most competitive fish detection network for our dataset, since it took a significantly shorter detection time while maintaining a high AP50 value of 0.85, compared to the best AP50 value of 0.86 being achieved by the combination of VGG16 with all improvement modules plus data augmentation. Overall, this work has verified the effectiveness of deep learning-based object detection methods and provided insights into subsequent network improvements.

Development and Core Technologies for Intelligent SWaP3 Infrared Cameras: A Comprehensive Review and Analysis.

With the development of infrared detection and imaging technology, infrared cameras (IRCs) play an important role in many fields, such as military, industry, and civilian. Additionally, the requirements for the size, performance, and intelligence of IRCs are becoming more and more strict. Consequently, the associated research and development (R&D) of IRCs is gradually focused on the aspects of miniaturization, high performance, intelligence, low power consumption, and low cost, involving many frontier fields, including artificial intelligence, new materials, new optical systems, and electronics systems. In fact, there are continual studies on intelligent SWaP3 IRCs, but unfortunately, a systematic arrangement and analysis are lacking. Therefore, a systematical and comprehensive review for the developments and core technologies of the intelligent SWaP3 IRCs is really needed. In this paper, in terms of the aforementioned requirements, we conduct a review and analysis of current intelligent SWaP3 IRCs based on 90 literature and statistics in recent decades to provide the relevant developers with a helpful reference for facilitating the indicator optimization of intelligent SWaP3 IRCs with new developed technologies. We analyze the development of SWaP3 IRCs in the aspects of lightweight, miniaturization, low price, and high performance, including hyperspectral resolution, high spatial resolution, large field of view (FOV), and wide dynamic elaborately. Moreover, the development in low power consumption and intelligence is also discussed in detail. Additionally, we briefly summarize the primary applications of intelligent SWaP3 IRCs in military, scientific, and civil. Then, the core technologies comprising high-integration, lightweight, hyperspectral imaging (HSI), low-power consumption, as well as the realization of high performance such as high-resolution, high-frame, and wide-dynamic range of SWaP3 IRCs are discussed and analyzed in detail. Finally, we prospect for the intelligent SWaP3 IRCs that it is necessary to continuously expand the concept of SWaP3 by reliability, stability, extensibility, and safety. In addition, it is useful to embed cutting-edge technologies such as small pixel pitch array, multi-sensors fusion, and deploy intelligent algorithms to IRCs. Additionally, the improvement of the whole machine from multi-dimension such as chip, camera, and system is expected and needs to be taken more seriously. It is hoped that this paper can provide a reference for the R&D of intelligent SWaP3 IRCs in the future.

Non-Contact Infrared Thermometers and Thermal Scanners for Human Body Temperature Monitoring: A Systematic Review.

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.

Continuous Structural Displacement Monitoring Using Accelerometer, Vision, and Infrared (IR) Cameras.

With the rapid development of computer vision, vision cameras have been used as noncontact sensors for structural displacement measurements. However, vision-based techniques are limited to short-term displacement measurements because of their degraded performance under varying illumination and inability to operate at night. To overcome these limitations, this study developed a continuous structural displacement estimation technique by combining measurements from an accelerometer with vision and infrared (IR) cameras collocated at the displacement estimation point of a target structure. The proposed technique enables continuous displacement estimation for both day and night, automatic optimization of the temperature range of an infrared camera to ensure a region of interest (ROI) with good matching features, and adaptive updating of the reference frame to achieve robust illumination-displacement estimation from vision/IR measurements. The performance of the proposed method was verified through lab-scale tests on a single-story building model. The displacements were estimated with a root-mean-square error of less than 2 mm compared with the laser-based ground truth. In addition, the applicability of the IR camera for displacement estimation under field conditions was validated using a pedestrian bridge test. The proposed technique eliminates the need for a stationary sensor installation location by the on-site installation of sensors and is therefore attractive for long-term continuous monitoring. However, it only estimates displacement at the sensor installation location, and cannot simultaneously estimate multi-point displacements which can be achieved by installing cameras off-site.

Definition of thermal indicators for the study of thermoregulation alterations in the foot of people living within diabetic peripheral neuropathy: A proof of concept.

AIMS: This study investigates how diabetic peripheral neuropathy is linked to impairment of thermoregulatory mechanisms using a thermal camera, spectral thermal analysis and a physical test. METHODS: The plantar skin temperature of all participants was measured using a thermal camera following a 6-min walking exercise. The data were subjected to frequency decomposition, resulting in two frequency ranges corresponding to endothelial and neurogenic mechanisms. Then, 40 thermal indicators were evaluated for each participant. ROC curve and statistical tests allowed to identify indicators able to detect the presence or absence of diabetic peripheral neuropathy. RESULTS: The study included 33 participants living with diabetes. The results revealed that a 6-min walk exercise increased plantar foot temperature and highlighted a significant difference between people living with diabetes with and without peripheral neuropathy (p < 0.01). The results also revealed the advantages of using thermal images rather than single point measurements. CONCLUSIONS: Diabetic peripheral neuropathy is linked to impairment of thermoregulatory mechanisms. This link can be highlighted after a dedicated 6-min walk exercise, enabling to activate these mechanisms, and measuring with a thermal camera the temporal plantar skin temperature. Assessment of this link gave best results by filtering the thermal signal in the neurogenic range.

Design of a Miniature Observation Robot for Light Emitting Diode Irradiation and Indocyanine Green Fluorescence-emission Guided Lymph Node Monitoring in Operating Rooms.

MOTIVATION: Typical surgical microscopes used for fluorescence-based lymph node detection experience limitations such as weight and restricted adjustability of the integrated light emitting diode (LED) and camera. This restricts the capture of detailed images of specific regions within the lesion. RESEARCH GOAL: This study proposes a miniature observation robot design that offers adjustable working distance (WD) and rotational radius, along with zoom-in/zoom-out functionality. METHODS: A five-degree-of-freedom manipulator was designed, with the end effector incorporating an LED and concave lens to widen the beam width for comprehensive lesion illumination. Additionally, a long-pass filter was integrated into the camera system to enhance image resolution. EXPERIMENTAL RESULTS: Experiments were conducted using a fluorescence-expressing phantom to evaluate the performance of the robot. Results demonstrated a captured image resolution of 9600 × 3240 pixels and a zoom-in/zoom-out capacity of up to 3.68 times. CONCLUSION: The proposed robot design is cost-effective and highly adjustable, enabling suitability for rapid and accurate detection of fresh lymph nodes during surgeries. The robot's capability to detect small lesions (<1 cm), as validated by phantom tests, holds promise for the detection of minute lymph nodes.

Crack Detection in Frozen Soils Using Infrared Thermographic Camera.

Frozen soils are encountered on construction sites in the polar regions or regions where artificial frozen ground (AFG) methods are used. Thus, efficient ways to monitor the behavior and potential failure of frozen soils are currently in demand. The advancement of thermographic technology presents an alternative solution as deformation occurring in frozen soils generate heat via inter-particle friction, and thus a subsequent increase in temperature. In this research, uniaxial compression tests were conducted on cylindrical frozen soil specimens of three types, namely clay, sand, and gravel. During the tests, surface temperature profiles of the specimens were recorded through an infrared video camera. The thermographic videos were analyzed, and subsequent results showed that temperature increases caused by frictional heat could be observed in all three frozen soil specimens. Therefore, increases in temperature can be deemed as an indicator for the potential failure of frozen soils and this method is applicable for monitoring purposes.

Skin Cancer Detection Using Infrared Thermography: Measurement Setup, Procedure and Equipment.

Infrared thermography technology has improved dramatically in recent years and is gaining renewed interest in the medical community for applications in skin tissue identification applications. However, there is still a need for an optimized measurement setup and protocol to obtain the most appropriate images for decision making and further processing. Nowadays, various cooling methods, measurement setups and cameras are used, but a general optimized cooling and measurement protocol has not been defined yet. In this literature review, an overview of different measurement setups, thermal excitation techniques and infrared camera equipment is given. It is possible to improve thermal images of skin lesions by choosing an appropriate cooling method, infrared camera and optimized measurement setup.

Real-Time Assessment of Mandarin Crop Water Stress Index.

The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level of water stress in plants continuously and to provide automatic sensing and controls. This research aimed at determining the viability, efficiency, and swiftness in employing the commercial Workswell WIRIS Agro R infrared camera (WWARIC) in monitoring water stress and scheduling appropriate irrigation regimes in mandarin plants. The experiment used a four-by-three randomized complete block design with 80−100% FC water treatment as full field capacity and three deficit irrigation treatments at 70−75% FC, 60−65% FC, and 50−55% FC. Air temperature, canopy temperature, and vapor pressure deficits were measured and employed to deduce the empirical crop water stress index, using the Idso approach (CWSI(Idso)) as well as baseline equations to calculate non-water stress and water stressed conditions. The relative leaf water content (RLWC) of mandarin plants was also determined for the growing season. From the experiment, CWSI(Idso) and CWSI were estimated using the Workswell Wiris Agro R infrared camera (CWSIW) and showed a high correlation (R2 = 0.75 at p < 0.05) in assessing the extent of water stress in mandarin plants. The results also showed that at an altitude of 12 m above the mandarin canopy, the WWARIC was able to identify water stress using three modes (empirical, differential, and theoretical). The WWARIC's color map feature, presented in real time, makes the camera a suitable device, as there is no need for complex computations or expert advice before determining the extent of the stress the crops are subjected to. The results prove that this novel use of the WWARIC demonstrated sufficient precision, swiftness, and intelligibility in the real-time detection of the mandarin water stress index and, accordingly, assisted in scheduling irrigation.

Segmentation of Plantar Foot Thermal Images Using Prior Information.

Diabetic foot (DF) complications are associated with temperature variations. The occurrence of DF ulceration could be reduced by using a contactless thermal camera. The aim of our study is to provide a decision support tool for the prevention of DF ulcers. Thus, the segmentation of the plantar foot in thermal images is a challenging step for a non-constraining acquisition protocol. This paper presents a new segmentation method for plantar foot thermal images. This method is designed to include five pieces of prior information regarding the aforementioned images. First, a new energy term is added to the snake of Kass et al. in order to force its curvature to match that of the prior shape, which has a known form. Second, we defined the initial contour as the downsized prior-shape contour, which is placed inside the plantar foot surface in a vertical orientation. This choice makes the snake avoid strong false boundaries present outside the plantar region when evolving. As a result, the snake produces a smooth contour that rapidly converges to the true boundaries of the foot. The proposed method is compared to two classical prior-shape snake methods, that of Ahmed et al. and that of Chen et al. A database of 50 plantar foot thermal images was processed. The results show that the proposed method outperforms the previous two methods with a root-mean-square error of 5.12 pixels and a dice similarity coefficient of 94%. The segmentation of the plantar foot regions in the thermal images helped us to assess the point-to-point temperature differences between the two feet in order to detect hyperthermia regions. The presence of such regions is the pre-sign of ulcers in the diabetic foot. Furthermore, our method was applied to hyperthermia detection to illustrate the promising potential of thermography in the case of the diabetic foot. Associated with a friendly acquisition protocol, the proposed segmentation method is the first step for a future mobile smartphone-based plantar foot thermal analysis for diabetic foot patients.

A Review of Infrared Thermography for Delamination Detection on Infrastructures and Buildings.

This paper provides a comprehensive review on the use of infrared thermography to detect delamination on infrastructures and buildings. Approximately 200 pieces of relevant literature were evaluated, and their findings were summarized. The factors affecting the accuracy and detectability of infrared thermography were consolidated and discussed. Necessary measures to effectively capture latent defects at the early stage of delamination before crack formation were investigated. The results of this study could be used as the benchmarks for setting standardized testing criteria as well as for comparison of results for future works on the use of infrared thermography for detection of delamination on infrastructures and buildings.

Reproducibility of skin temperature analyses by novice and experienced evaluators using infrared thermography.

Infrared thermography (IRT) has become popular in several areas of knowledge. However, the analyses of thermal images often request manual actions, and little is known about the effect of the evaluator's experience on analysis thermal images. Here, we determine the reproducibility of IRT images analysis performed by evaluators with different levels of experience. Eight evaluators (GE, group experienced, n = 4; GN, group novice, n = 4) analyzed thermograms from 40 healthy participants recorded before and after exercise to determine the mean, minimum, maximum, standard deviation, and range of skin temperature in the anterior thigh and posterior leg. Before and after exercise, mean temperature showed excellent reproducibility for both groups for the anterior thigh (ICC >0.98) and posterior leg (ICC >0.94), and maximum temperature showed excellent reproducibility for both groups in the posterior leg (ICC >0.91). The influence of experience level was not significant considering the anterior thigh. Similarly, experience level did not affect the mean, maximum, and standard deviation temperature determined for the posterior leg. For the posterior leg, minimum temperature presented lower values and the range was higher among novice evaluators. Mean skin temperature showed narrower 95% limits of agreement than minimum and maximum for both regions and moments. Caution is advised when temperature ranges and minimums are determined by different evaluators. We conclude that for IRT analysis by evaluators with different levels of experience, the mean and maximum temperatures should be prioritized due to their better reproducibility.

An exploratory experiment using temperature drop curve features to identify activity information of duck eggs at mid-incubation.

To address the problem that duck egg mortality is not easily detected at mid-incubation, this paper explored a method to detect mid-incubation egg activity information based on temperature drop curve (TDC) features. In this paper, we used a thermal infrared camera to obtain continuous thermal images of death fertilized duck eggs (DFDE) on the 16th day of incubation and alive fertilized duck eggs (AFDE) hatched for 16-19 days in a 20 °C environment. By observing the temperature drop curve of egg surface, we extracted and visualized five features that could reflect the activity information of duck eggs. And we used K-Nearest Neighbor (KNN), Naive Bayesian (NB) and Support Vector Machine (SVM) to establish the activity information detection models for different incubation days. The results showed that KNN could better distinguish the activity of eggs at the 16th and the 17th day of incubation, with F1-score of 85.43% and 85.98%, respectively. The SVM showed better results at the 18th and the 19th day of incubation, with F1-score of 90.57% and 96.3%, respectively. The experimental results demonstrated that the activity detection method based on the temperature drop curve features in this paper could efficiently and nondestructively detect the activity information of mid-incubation duck eggs, which provided a technical foundation for detecting the activity information of duck eggs at mid-incubation.

'Dual-reference' method for high-precision infrared measurement of leaf surface temperature under field conditions.

Temperature is a key control over biological activities from the cellular to the ecosystem scales. However, direct, high-precision measurements of surface temperature of small objects, such as leaves, under field conditions with large variations in ambient conditions remain rare. Contact methods, such as thermocouples, are prone to large errors. The use of noncontact remote-sensing methods, such as thermal infrared measurements, provides an ideal solution, but their accuracy has been low (c. 2°C) owing to the necessity for corrections for material emissivity and fluctuations in background radiation Lbg . A novel 'dual-reference' method was developed to increase the accuracy of infrared needle-leaf surface temperature measurements in the field. It accounts for variations in Lbg and corrects for the systematic camera offset using two reference plates. We accurately captured surface temperature and leaf-to-air temperature differences of needle-leaves in a forest ecosystem with large diurnal and seasonal temperature fluctuations with an uncertainty of ± 0.23°C and ± 0.28°C, respectively. Routine high-precision leaf temperature measurements even under harsh field conditions, such as demonstrated here, opens the way for investigating a wide range of leaf-scale processes and their dynamics.

Fluorescence Imaging of Tumor-Accumulating Antibody-IR700 Conjugates Prior to Near-Infrared Photoimmunotherapy (NIR-PIT) Using a Commercially Available Camera Designed for Indocyanine Green.

Near-infrared photoimmunotherapy (NIR-PIT) is a newly developed cancer treatment that uses antibody-IRDye700DX (IR700) conjugates and was recently approved in Japan for patients with inoperable head and neck cancer. Exposure of the tumor with NIR light at a wavelength of 690 nm leads to physicochemical changes in the antibody-IR700 conjugate-cell receptor complex, resulting in increased hydrophobicity and damage to the integrity of the cell membrane. However, it is important that the tumor be completely exposed to light during NIR-PIT, and thus, a method to provide real-time information on tumor location would help clinicians direct light more accurately. IR700 is a fluorophore that emits at 702 nm; however, there is no clinically available device optimized for detecting this fluorescence. On the other hand, many indocyanine green (ICG) fluorescence imaging devices have been approved for clinical use in operating rooms. Therefore, we investigated whether LIGHTVISION, one of the clinically available ICG cameras, could be employed for NIR-PIT target tumor detection. Due to the limited benefits of adding IR700 molecules, the additional conjugation of IRDye800CW (IR800) or ICG-EG4-Sulfo-OSu (ICG-EG4), which has an overlapping spectrum with ICG, to trastuzumab-IR700 conjugates was performed. Conjugation of second NIR dyes did not interfere the efficacy of NIR-PIT. The dual conjugation of IR800 and IR700 to trastuzumab clearly visualized target tumors with LIGHTVISION by detecting emission light of IR800. We demonstrated that the conjugation of second NIR dyes enables us to provide a real-time feedback of tumor locations prior to NIR-PIT.

A general model of the thermal constraints on the world's most destructive locust, Schistocerca gregaria.

All terrestrial ectotherms are constrained to some degree by their thermal environment and the extent to which they can behaviorally buffer variable thermal conditions. New biophysical modeling methods (NicheMapR) allow the calculation of the body temperature of thermoregulating animals anywhere in the world from first principles, but require detailed observational data for parameterization and testing. Here we describe the thermoregulatory biology of marching bands of the desert locust, Schistocerca gregaria, in the Sahara Desert of Mauritania where extreme heat and strong diurnal fluctuations are a major constraint on activity and physiological processes. Using a thermal infrared camera in the field, we showed that gregarious nymphs altered the microhabitats they used, as well as postural thermoregulatory behaviors, to maintain relatively high body temperature (nearly 40°C). Field and laboratory experiments demonstrated that the preferred body temperature accelerated digestive rates. Migratory bands frequently left foraging sites with full guts before consuming all vegetation and moved to another habitat before emptying their foregut. Thus, the repertoire for behavioral thermoregulation in the desert locust strongly facilitates foraging and digestion rates, which may accelerate developmental rates and increase survival. We used our data to successfully parameterize a general biophysical model of thermoregulatory behavior that could capture hourly body temperature and activity at our remote site using globally available environmental forcing data. This modeling approach provides a stronger basis for forecasting thermal constraints on locust outbreaks under current and future climates.

Bi-Spectral Infrared Algorithm for Cloud Coverage over Oceans by the JEM-EUSO Mission Program.

The need to monitor specific areas for different applications requires high spatial and temporal resolution. This need has led to the proliferation of ad hoc systems on board nanosatellites, drones, etc. These systems require low cost, low power consumption, and low weight. The work we present follows this trend. Specifically, this article evaluates a method to determine the cloud map from the images provided by a simple bi-spectral infrared camera within the framework of JEM-EUSO (The Joint Experiment Missions-Extrem Universe Space Observatory). This program involves different experiments whose aim is determining properties of Ultra-High Energy Cosmic Ray (UHECR) via the detection of atmospheric fluorescence light. Since some of those projects use UV instruments on board space platforms, they require knowledge of the cloudiness state in the FoV of the instrument. For that reason, some systems will include an infrared (IR) camera. This study presents a test to generate a binary cloudiness mask (CM) over the ocean, employing bi-spectral IR data. The database is created from Moderate-Resolution Imaging Spectroradiometer (MODIS) data (bands 31 and 32). The CM is based on a split-window algorithm. It uses an estimation of the brightness temperature calculated from a statistical study of an IR images database along with an ancillary sea surface temperature. This statistical procedure to obtain the estimate of the brightness temperature is one of the novel contributions of this work. The difference between the measured and estimation of the brightness temperature determines whether a pixel is cover or clear. That classification requires defining several thresholds which depend on the scenarios. The procedure for determining those thresholds is also novel. Then, the results of the algorithm are compared with the MODIS CM. The agreement is above 90%. The performance of the proposed CM is similar to that of other studies. The validation also shows that cloud edges concentrate the vast majority of discrepancies with the MODIS CM. The relatively high accuracy of the algorithm is a relevant result for the JEM-EUSO program. Further work will combine the proposed algorithm with complementary studies in the framework of JEM-EUSO to reinforce the CM above the cloud edges.

Plant Leaf Detection and Counting in a Greenhouse during Day and Nighttime Using a Raspberry Pi NoIR Camera.

A non-destructive method using machine vision is an effective way to monitor plant growth. However, due to the lighting changes and complicated backgrounds in outdoor environments, this becomes a challenging task. In this paper, a low-cost camera system using an NoIR (no infrared filter) camera and a Raspberry Pi module is employed to detect and count the leaves of Ramie plants in a greenhouse. An infrared camera captures the images of leaves during the day and nighttime for a precise evaluation. The infrared images allow Otsu thresholding to be used for efficient leaf detection. A combination of numbers of thresholds is introduced to increase the detection performance. Two approaches, consisting of static images and image sequence methods are proposed. A watershed algorithm is then employed to separate the leaves of a plant. The experimental results show that the proposed leaf detection using static images achieves high recall, precision, and F1 score of 0.9310, 0.9053, and 0.9167, respectively, with an execution time of 551 ms. The strategy of using sequences of images increases the performances to 0.9619, 0.9505, and 0.9530, respectively, with an execution time of 516.30 ms. The proposed leaf counting achieves a difference in count (DiC) and absolute DiC (ABS_DiC) of 2.02 and 2.23, respectively, with an execution time of 545.41 ms. Moreover, the proposed method is evaluated using the benchmark image datasets, and shows that the foreground-background dice (FBD), DiC, and ABS_DIC are all within the average values of the existing techniques. The results suggest that the proposed system provides a promising method for real-time implementation.

FLIR vs SEEK thermal cameras in biomedicine: comparative diagnosis through infrared thermography.

BACKGROUND: In biomedicine, infrared thermography is the most promising technique among other conventional methods for revealing the differences in skin temperature, resulting from the irregular temperature dispersion, which is the significant signaling of diseases and disorders in human body. Given the process of detecting emitted thermal radiation of human body temperature by infrared imaging, we, in this study, present the current utility of thermal camera models namely FLIR and SEEK in biomedical applications as an extension of our previous article. RESULTS: The most significant result is the differences between image qualities of the thermograms captured by thermal camera models. In other words, the image quality of the thermal images in FLIR One is higher than SEEK Compact PRO. However, the thermal images of FLIR One are noisier than SEEK Compact PRO since the thermal resolution of FLIR One is 160 × 120 while it is 320 × 240 in SEEK Compact PRO. CONCLUSION: Detecting and revealing the inhomogeneous temperature distribution on the injured toe of the subject, we, in this paper, analyzed the imaging results of two different smartphone-based thermal camera models by making comparison among various thermograms. Utilizing the feasibility of the proposed method for faster and comparative diagnosis in biomedical problems is the main contribution of this study.

Fully Automated Lab-On-A-Disc Platform for Loop-Mediated Isothermal Amplification Using Micro-Carbon-Activated Cell Lysis.

Fast and fully automated deoxyribonucleic acid (DNA) amplification methods are of interest in the research on lab-on-a-disc (LOD) platforms because of their full compatibility with the spin-column mechanism using centrifugal force. However, the standard procedures followed in DNA amplification require accurate noncontact temperature control as well as cell lysis at a low temperature to prevent damage to the LOD platform. This requirement makes it challenging to achieve full automation of DNA amplification on an LOD. In this paper, a fully automated LOD capable of performing cell lysis and amplification on a single compact disc of DNA samples is proposed. The proposed system uses micro-carbon to heat DNA samples without damaging the LOD as well as a noncontact heating system and an infrared camera sensor to remotely measure the real temperature of the amplification chamber. Compared with conventional DNA amplification systems, the proposed system has the advantage of full automation of the LOD platform. Experimental results demonstrated that the proposed system offers a stable heating method for DNA amplification and cell lysis.