• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.33-38
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• 2005

In this paper, the sensing unit of a non-invasive blood glucose sensor for home users, using a magneto-resonance absorption method, have been designed and manufactured. The sensor is capable of non-invasively determining blood glucose levels through measuring the 1H spin-lattice relaxation time in human body, The comparison of initial models, with different dimensions and shapes, for the sensing unit has led us to select the materials of the final model, which has adequate size and weight for home use. Through the design optimization using the FEM model, the dimension of final model has been determined to satisfy the required strength and uniformity of the magnetic field in the detecting area.

• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.291-294
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• 2014

In this study, a chemiresistive sensor based on one-dimensional $WO_3$ nanostructures is presented for application in non-invasive medical diagnostics. $WO_3$ nanostructures were used as an active gas sensing layer and were deposited onto a $SiO_2/Si$substrate using Pt interdigitated electrodes (IDEs). The IDE spacing was $5{\mu}m$ and deposition was performed using RF sputter with glancing angle deposition mode. Pt IDEs fabricated by photolithography and dry etching. In comparison with thin film sensor, sensing performance of nanostructure sensor showed an enhanced response of more than 20 times when exposed to 50 ppm acetone at $400^{\circ}C$. Such a remarkable faster response can pave the way for a new generation of exhaled breath analyzers based on chemiresistive sensors which are less expensive, more reliable, and less complicated to be manufactured. Moreover, presented sensor technology has the potential of being used as a personalized medical diagnostics tool in the near future.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.28-34
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• 2018

This paper is composed of a passenger management system using a temperature sensing module, a PIR sensor module for detecting movement inside a room, and a smart breath sensing module for determining a sleeping state. An embedded sensor module and a communication system integrated the sensing part and the algorithm driving part. As the aging society is accelerating and becoming more upgraded, the social cost of Silver Care increases, and in order to protect privacy, it is necessary to reduce costs by developing efficient smart silver care devices. The proposed non - image human body detection IOT sensor system is implemented by hardware and software and has superior performance compared with conventional image monitoring method.

• Journal of Biomedical Engineering Research
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• v.33 no.3
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• pp.114-127
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• 2012

Recent technical advancement allows noninvasive measurement of blood glucose. In this literature, we reviewed various noninvasive techniques for measuring glucose concentration. Optical or electrical methods have been investigated. Optical techniques include near-infrared spectroscopy, Raman spectroscopy, optical coherence technique, polarization, fluorescence, occlusion spectroscopy, and photoacoustic spectroscopy. Electrical methods include reverse iontophoresis, impedance spectroscopy, and electromagnetic sensing. Ultrasound, detection from breath, or fluid harvesting technique can be used to measure blood glucose level. Combination of various methods is also promising. Although there are many interesting and promising technologies and devices, there need further researches until a commercially available non-invasive glucometer is popular.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.991-1000
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• 2021

Among non-invasive blood glucose detection technologies, the optical technique is a method that uses light reflection, absorption, and scattering characteristics when passing through a biological medium. It reduces pain or discomfort in measurement and has no risk of infection. So it is becoming a major flow of blood glucose detection research. Among them, near-infrared spectroscopy has a disadvantage in that the complexity increases when analyzing signals detected due to interferences between proteins and acids that share a similar absorption function with blood glucose molecules. In this study, a non-invasive sensor system with multiple near-infrared bands was designed and manufactured to alleviate the deterioration of blood glucose detection function that may occur due to skin absorption of near-infrared rays. A blood survey was conducted to verify the system, and the degree of blood glucose response in the blood was collected as spectral data, and the results of this study were quantitatively verified in terms of correlation between the data and blood glucose.

• The Plant Pathology Journal
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• v.34 no.6
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• pp.459-469
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• 2018

Plants and microorganisms (microbes) use information from chemicals such as volatile compounds to understand their environments. Proficiency in sensing and responding to these infochemicals increases an organism's ecological competence and ability to survive in competitive environments, particularly with regard to plant-pathogen interactions. Plants and microbes acquired the ability to sense and respond to biogenic volatiles during their evolutionary history. However, these signals can only be interpreted by humans through the use of state-of the-art technologies. Newly-developed tools allow microbe-induced plant volatiles to be detected in a rapid, precise, and non-invasive manner to diagnose plant diseases. Beside disease diagnosis, volatile compounds may also be valuable in improving crop productivity in sustainable agriculture. Bacterial volatile compounds (BVCs) have potential for use as a novel plant growth stimulant or as improver of fertilizer efficiency. BVCs can also elicit plant innate immunity against insect pests and microbial pathogens. Research is needed to expand our knowledge of BVCs and to produce BVC-based formulations that can be used practically in the field. Formulation possibilities include encapsulation and sol-gel matrices, which can be used in attract and kill formulations, chemigation, and seed priming. Exploitation of biogenic volatiles will facilitate the development of smart integrated plant management systems for disease control and productivity improvement.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.1-16
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• 2019

Dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging plays an important role in non-invasive detection and characterization of primary and metastatic lesions in the liver. Recently, efforts have been made to improve spatial and temporal resolution of DCE liver MRI for arterial phase imaging. Review of recent publications related to arterial phase imaging of the liver indicates that there exist primarily two approaches: breath-hold and free-breathing. For breath-hold imaging, acquiring multiple arterial phase images in a breath-hold is the preferred approach over conventional single-phase imaging. For free-breathing imaging, a combination of three-dimensional (3D) stack-of-stars golden-angle sampling and compressed sensing parallel imaging reconstruction is one of emerging techniques. Self-gating can be used to decrease respiratory motion artifact. This article introduces recent MRI technologies relevant to hepatic arterial phase imaging, including differential subsampling with Cartesian ordering (DISCO), golden-angle radial sparse parallel (GRASP), and X-D GRASP. This article also describes techniques related to dynamic 3D image reconstruction of the liver from golden-angle stack-of-stars data.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.995-999
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• 2015

Inductive sensors are versatile and economical devices that are widely used to measure a wide variety of physical variables, such as displacement, force, and pressure. In this paper, we propose a simple inductive sensor consisting of a thin partial ring and a coil set. The self-inductance of the sensor was estimated using magnetic circuit analysis and validated through finite element analysis (FEA). The natural frequency of the ring was estimated using Castigliano's theorem and the method of equivalent mass. The estimation was validated through experiments and FEA. A prototype sensor with a signal processing circuit is built and applied to noninvasively sense the pressure inside a flexible tube. The obtained sensor outputs show quadratic behavior with respect to the pressure. When fitted to a quadratic equation, the least-square measurement error was less than 2%. The results confirm the feasibility of pressure sensing using the proposed inductive sensor.

• Ceramist
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• v.22 no.1
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• pp.70-81
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• 2019

Breath analysis is rapidly evolving as a non-invasive disease recognition and diagnosis method. Metal oxide gas sensors are one of the most ideal platforms for realizing portable, hand-held breath analysis devices in the near future. This paper reviewed the recent developments in metal oxide gas sensors detecting exhaled biomarker gases such as nitric oxides, acetone, ammonia, hydrogen sulfide, and hydrocarbons. Emphasis was placed on strategies to tailor sensing materials/films capable of highly selective and sensitive detection of biomarker gases with negligible cross-response to ethanol, the major interfering breath gas. Specific examples were given to highlight the validity of the strategies, which include optimization of sensing temperature, doping additives, utilizing acid-base interaction, loading catalysts, and controlling gas reforming reaction. In addition, we briefly discussed the design and optimization method of gas sensor arrays for implementing the simultaneous assessment of multiple diseases. Breath analysis using high-performance metal oxide gas sensors/arrays will open new roads for point-of-care diagnosis of diseases such as asthma, diabetes, kidney dysfunction, halitosis, and lung cancer.