Ki-Young Shin

Development of a radial pulse tonometric (RPT) sensor with a temperature compensation mechanism.

Several RPT sensors have been developed to acquire objective and quantitative pulse waves. These sensors offer improved performance with respect to pressure calibration, size and sensor deployment, but not temperature. Since most pressure sensors are sensitive to temperature, various temperature compensation techniques have been developed, but these techniques are largely inapplicable to RPT sensors due to the size restrictions of the sensor, and incompatibility between the compensation techniques and the RPT sensor. Consequently, in this paper a new RPT sensor comprising six piezoresistive pressure sensors and one thermistor has been developed through finite element analysis and then a suitable temperature compensation technique has been proposed. This technique compensates for temperature variations by using the thermistor and simple compensation equations. As verification of the proposed compensation technique, pulse waves of all types were successfully compensated for temperature changes.

Development of a Preamplifier and a Wireless Surface EMG

The primary objective of this study was to develop a preamplifier and a wireless surface EMG of a noninvasive type. The limitations of the existing system include its large size and the necessity of a wire. Therefore, this study focused on the development of a preamplifier which includes three electrodes and a wireless EMG. The EMG described herein is comprised of a preamplifier including an electrode for the measurement of the EMG signal, a main amplifier for signal processing, an A/D converter, and a Bluetooth module for wireless communication. The developed EMG utilized a UART (Universal Asynchronous serial Receiver and Transmitter) and Bluetooth protocols for communication. The sampling frequency of this system is 1,024 Hz. The developed EMG signal has relatively favorable characteristics as compared with current commercially available EMG systems. In our power spectral density analysis, the EMG signal was distributed between approximately 70 Hz and 200 Hz, and between approximately 10 Hz and about 50 Hz.

Methodology for Force Measurement Using Piezoelectric Ceramic

Currently, the shift of the resonant frequency of a PZT (Lead zirconate titanate) ceramic is required for pressure measurement. In order to measure the resonant frequency in each load, however, both a frequency generator and an impedance analyzer must be applied. The primary objective of this study is to develop a new methodology which is cost-effective and simple, as compared to the currently-used method for pressure measurement, using a PZT ceramic. In the methodology developed herein, we have measured the change in the impedance of each load when a fixed frequency, the anti-resonance frequency, was applied to the PZT ceramic. Impedance changes can be measured according to changes of current via Ohm’s law, and thus pressure was measured by voltage in the PZT ceramic. The load was increased from 0 kg to 3 kg, and the result, measured in voltage, and the experimental results yielded a regression equation of y=1.2069x+0.3706 and an r-square value of 0.9765.

An improved method for energy calibration of photon counting X-ray detectors

Photon counting X-ray detectors with energy discrimination capabilities can discriminate the energy of incident X-ray photon, thereby spectral imaging is possible with them. Energy calibration is a process to find a linear mapping function between the amplitudes of electric pulses and their corresponding photon energy. For practical and efficient energy calibration, the X-ray tube voltage can be used as a reference. However, as the exposure time increases, the threshold giving 50 % of OFF pixels also increases without converging to a point. To reduce calibration errors due to this non-convergent behavior, we present an improved method for energy calibration with applying it to two commercial photon counting X-ray detectors, i.e., a CdTe Medipix2 detector and a CdTe Pixirad2 detector with PFXIE-II read-out ASIC. With the improved mapping function estimated by the improved method, we can better identify the iodine component in a phantom consisting of iodine and other components.

Rotational Characteristics of Target Registration Error for Contour-based Registration in Neuronavigation System: A Phantom Study

Abstract: In this study, we investigated the rotational characteristics which were comprised of directionality and lin-earity of target registration error (TRE) as a study in advance to enhance the accuracy of contour-based registrationin neuronavigation. For the experiment, two rigid head phantoms that have different faces with specially designedtarget frame fixed inside of the phantoms were used. Three-dimensional coordinates of facial surface point cloud andtarget point of the phantoms were acquired using computed tomography (CT) and 3D scanner. Iterative closest point(ICP) method was used for registration of two different point cloud and the directionality and linearity of TRE in over-all head were calculated by using 3D position of targets after registration. As a result, it was represented that TREhad consistent direction in overall head region and was increased in linear fashion as distance from facial surface,but did not show high linearity. These results indicated that it is possible for decrease TRE by controlling orientationof facial surface point cloud acquired from scanner, and the prediction of TRE from surface registration error candecrease the registration accuracy in lesion. In the further studies, we have to develop the contour-based registrationmethod for improvement of accuracy by considering rotational characteristics of TRE.Key words: Neuronavigation, Image-guided surgery, Contour-based registration, Target registration error, Rota-tional characteristics

Tibiofemoral Kinematic Analysis Using Contact Model during Normal Gait

The geometry of the articular surface is extremely important in kinematic analysis, and the 6-DOF joint model is required for an accurate understanding of the functionality of the knee joint in vivo. However, only a few previous studies have utilized the 6-DOF knee joint model, but even in these studies the geometry of the articular surface has been simplified. Thus, we developed a 6-DOF contact model of the human knee joint with realistic geometry, approximated by a non-uniform B-spline, and conducted tibiofemoral kinematic analysis during normal gait using the contact model. The contact point on the femoral condyle shifted posteriorly with knee flexion. In addition, the contact area of the medial condyle was larger than that of the lateral condyle. These results were reasonably consistent with the results of previous studies. According to the results of the tibiofemoral kinematic analyses of six healthy male subjects, the standard deviation of the contact points ranged from ± 0.0145 cm at a 15° flexion to ± 0.1412 cm at 40° on the medial condyle and from ± 0.0046 cm at a 15° flexion to ± 0.1793 cm at 40° on the lateral condyle. The contact points had a very similar pattern as a whole, although six subjects exhibited different gait pattern except for flexion/extension.

The Effect of Cardiovascular System According to The Hot Water-Induced Stimulation on Foot

In this paper, we applied a hot water-induced thermotherapy system to the foot, based on the oriental medicine principle of Dongeuibogam, which is concerned with the notion that the head should be kept cool and the feet warm. The objective of this study was to determine the influence on the cardiovascular system effected by physiological parameters inherent to thermal stimulation at a temperature of 43°C. Therefore, the relevant physiological parameters, blood flow, heart rate, blood pressure, oxygen saturation, and leg temperature, associated with the cardiovascular system, were selected for analysis. The experimental equipment used in this study included a hot water system designed for the feet. Pre and post experimental conditions, at a temperature of 43°C, were assessed for 10 healthy volunteers over 10 days. Pre and post measurements were obtained at 5, 10, 15, and 20 minutes. The biosignal transition results of the experiments were as follows; Blood Flow(ml/min): 1.18 ± 0.50 inc, Heart Rate(bpm): 6.97 ± 0.72 inc, Blood Pressure(mmHg): (max) −1.49 ± 2.81 dec, (min) −0.06 ± 0.13 dec, Oxygen Saturation(%): 1.34 ± 0.28 inc, (dec: decrease, inc: increase). According to our results, hot-water thermotherapy applied to the foot does appear to exert an influence on the cardiovascular system, and also appears to generally improve human metabolism.

A Study on Chronic Glomerulonephritis Discrimination of Clinical Urine Analysis Data Using Neural Network

Chronic glomerulonephritis (CGN), which is caused by an inflammation of the kidney, can be diagnosed via urine, X-ray and biopsy. The objective of this paper was to present an method for the automatic discrimination of clinical test data of CGN patients via a urine analyzer, independently of an inspector’s visual inspection, using both statistical methods and a neural network. 10 parameters on a urine strip pad were utilized in order to diagnose disease during the urine test. The indicators of strip pads explain the meanings of the reacted color levels of urobilinogen, glucose, ketones, bilirubin, protein, nitrite, pH, occult blood, specific gravity and leukocytes. In order to detect CGN using the neural network, 4 parameters which are without statistic significance regarding CGN are removed via chi-square and t-tests. The input layer of the neural network consists of a reduced number of 6 parameters and the output layer is used to determine whether or not the given sample is dispositive for CGN. The learning process involved training with the data from 73 normal and 66 CGN patients. The validation set consisted of 50 normals and 50 patients, and was not used in the training set. The neural network was able to discriminate correctly in 96 percent of the normal patients and 94 percent of the CGN patients. Tests of statistic significance and the application of such a neural network appear to be quite effective with regard to the discrimination of CGN.