• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2005년도 추계종합학술대회
• /
• pp.489-492
• /
• 2005

Even though the blood pressure is one of the most widely used index for the healthcare monitoring of hypertensive and normotensive persons, there is no non-intrusive measurement method which is commercialized until now. Pulse Arrival Time (PAT) is known that it has close relation with the systolic blood pressure (SBP) and arterial stiffness. In this study, SBP estimation methods by non-intrusive measurement of PAT are suggested. For the unconstrained measurement of PAT, the first method used the electrically non contact electrocardiogram (ENC-ECG) technique and the reflective type of Photoplethysmography (PPG) sensor on the computer mouse. In the second method, ENC-ECG and the air pressure sensor in the seat cushion on a chair were measured. The third method used ECG electrodes and PPG sensors on the toilet seat cover. The validation and regression analysis of the relationship of PAT and SBP are summarized. These methods have considerable errors to be used for all people. But these can be applied for each subject after the parameter customization within acceptable error. So, it is feasible for suggested methods to be used for monitoring of SBP in daily life in non-intrusive way when there is personal identification system of each subject.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
• /
• pp.413-415
• /
• 2006

Wire rods are carried by C-Hooks and are tracked by bringing the inspection sensors into contact with steel bars on the C-Hooks. However, the conventional system using mechanical equipment is not reliable due to aging, wearing and bending of steel bars. To overcome these problems, a non-contact type identification system is required. This paper introduces the radio frequency identification(RFID) technology which is one of the most popular non-contact identification methods, and evaluates its performance in the real environment of POSCO. Specifically, we use tags which are designed for operating on high temperature and allowing easy attaching and detaching on the C-Hook. A new monitoring program is developed for reacting upon the conventional system and showing the results of reading of reading tags.

• Smart Structures and Systems
• /
• 제24권6호
• /
• pp.723-732
• /
• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

• 한국생산제조학회지
• /
• 제4권2호
• /
• pp.38-45
• /
• 1995

The diagnosis and monitoring system of abnormal cutting condition is necessary to realize precision machining proces and factory automation, which are final goal of metal cutting in order to develop this system, theimage processing technique has been investigated in machining process. In theis paper, the measurement system of tool wear using computer vision is designed to detect the wear pattern by non-contact and direct method and get the realiable wear information about cutting tool. We measured the area of the side and front part of the diamond core dril which is used in 40kHz ultrasonic vibration machine.

• 공학교육연구
• /
• 제17권4호
• /
• pp.15-20
• /
• 2014

The non-contact easy detecting system of nursing person's body vital information and their behaviors monitoring system are developed, which consist of "Kinect" sensor and thermography camera. The "Kinect" sensor can catch the body contour and the body moving behavior, and output their imaging data realtime. The thermography camera can detect respiration state and body temperature, etc. In this study, the practicability of this system was verified.

• 대한의용생체공학회:의공학회지
• /
• 제38권5호
• /
• pp.264-270
• /
• 2017

A Doppler radar sensor was applied to detect respirations and heartbeats of persons who were lying on a bed. This study is preliminary study aiming at non-contact and non-intrusive respiration and heart rate monitoring during sleep in daily life. For the experiments, 10GHz Doppler radar with patch-type antenna was used and installed on the upper right and the distance between the body and the antenna was 1 m. The results show that each signal of respiration and heartbeat is observed in each frequency band however the frequency band and the waveform vary according to the subjects and the posture. The results show that the heartbeats can be detected with the peak detection in some frequency band. This study shows the feasibility of applying the Doppler radar to detection of heartbeat and respiration during sleep and further studies about heartbeat detection algorithm are required.

• 한국정밀공학회지
• /
• 제31권2호
• /
• pp.141-148
• /
• 2014

In this work, effects of plasma on different hardness of welding steel using laser-induced breakdown spectroscopy were investigated. The ratios of ionic to atomic spectrum peaks were related to its material hardness. The major spectrum peak (Fe) and minor spectrum peak (Mn) were considered as monitoring elements. The stronger repulse plasma was generated, the harder material it was. The ratios of ionic to atomic spectrum peaks increased with respect to the material hardness as well. The correlation of minor spectrum peaks was stronger than that of major spectrum peaks. However, the major spectrum peaks indicated a similar trend, which could be used to estimate the hardness, too. Based on this result, the method could be used as a non-contact remote measurement of material properties.

• 대한임베디드공학회논문지
• /
• 제18권6호
• /
• pp.277-283
• /
• 2023

Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.

• 한국정밀공학회지
• /
• 제4권2호
• /
• pp.36-46
• /
• 1987

An optical technique using laser for non-contact measurement of surface roughness and form accuracy of ground surfaces is presented. It is found that, when a ground surface is illuminated by a beam of laser light, the roughness height and slope distribution has significant influence on the pattern of reflection and it maintains an unique Gaussian distribution relationship with the surface roughness. The principle idea of the optical measurement system is therefore monitor the radiation, and then calibrate it in process against surface roughness by means of necessary digital data processing. On the other hand, measuring the form accuracy of a ground surface is accomplished by using a triangular method, which is based on observing the movement of an image of a spot of light projected onto the surface. The image is focused, through a series of lenses for magnification, on a photodetector array lf line configur- ation. Then the relative movement of image and consequently the form accuracy of the surface can be obtained through appropriate calibration procedures. Experimental test showed that the optical roughness measurement technique suggested in this work is very efficient for most industrial applications being capable of monitoring the roughness heights ranging 0.1 to 0.6 .$\mu$m CLA values. And form accuracy can be measured in process with a resolution of 10 .$\mu$m.

• 대한의용생체공학회:의공학회지
• /
• 제37권5호
• /
• pp.178-185
• /
• 2016

Tear is a promising biological fluid for non-invasive health monitoring. It has been studied in the past to be a possible candidate for the diagnosis of certain systemic diseases, such as breast cancer, multiple sclerosis, prostate cancer, and diabetes. However, currently existing methods for collecting and extracting tear from the human eye causes inconsistencies in the biomolecule concentrations of the tear sample due to the irritating nature of the process. In response, we designed and fabricated a microfluidic system embedded soft contact-lens for the purpose of tear sampling. The lens was then tested with artificial tear for its tear sampling capability, and found to be able to find concentration equilibrium within 50 minutes. Additionally, simulation was carried out to further optimize the design so that tear sampling rate matched the natural tear turn-over rate of 1 microliter per minute.