I.Y. Kim

Measurement of femoral neck anteversion in 3D. Part 2:3D modelling method

Femoral neck anteversion is the torsion of the femoral head with reference to the distal femur. Conventional methods that use cross-sectional computed tomography (CT), magnetic resonance or ultrasound images to estimate femoral anteversion have met with several problems owing to the complex, three-dimensional (3D) structure of the femur. These problems include not only the difficulty of defining the direction of the femoral neck axis and condylar line but also the dependency upon patient positioning. In particular, the femoral neck axis, the direction of the femoral head, known as the major source of error, is difficult to determine from either a single or several two-dimensional (2D) cross-sectional images. A new method has been devised for the measurement of femoral anteversion using the 3D imaging technique. 3D reconstructed CT images from the femoral head and trochanter to the distal femur are used to measure the anteversion. It is necessary to remove the soft tissue from the CT images and extract just the bone part. Then, the femoral anteversion is measured from a computer-rendered femur image. The 3D imaging method is compared with both the conventional 2D method and the physical method using 20 dried femurs. For the physical method, which is used as a reference value, a special apparatus is devised. The average difference between the results of the physical method and those of the 2D CT method is 5.33°. The average difference between the results of the physical method and those of the 3D imaging method is 0.45°. Seventy-four patients, who suffer from toe-in-gait disease, are tested to compare the 3D imaging method with the conventional 2D CT method. The average difference between the 2D and 3D methods is 8.6°, and the standard is 7.43°. This method provides a very accurate and reliable measurement of femoral anteversion, as it is virtually equivalent to the direct measurement of bisected dried femur in vitro.

Hierarchical support vector machine based heartbeat classification using higher order statistics and hermite basis function

The heartbeat class detection of the electrocardiogram is important in cardiac disease diagnosis. For detecting morphological QRS complex, conventional detection algorithm have been designed to detect P, QRS, T wave. However, the detection of the P and T wave is difficult because their amplitudes are relatively low, and occasionally they are included in noise. We applied two morphological feature extraction methods: higher-order statistics and Hermite basis functions. Moreover, we assumed that the QRS complexes of class N and S may have a morphological similarity, and those of class V and F may also have their own similarity. Therefore, we employed a hierarchical classification method using support vector machines, considering those similarities in the architecture. The results showed that our hierarchical classification method gives better performance than the conventional multiclass classification method. In addition, the Hermite basis functions gave more accurate results compared to the higher order statistics.

Continuous measurement of systolic blood pressure using the PTT and other parameters

In this paper, we proposed the regression model which could estimate unspecified peoples systolic blood pressure (SBP) conveniently and continuously and checked its accuracy through clinical experiments. The method for estimating each individual SBP by using only pulse transit time (PTT) has been studied, but it is difficult to estimate unspecified peoples SBP with the method using only PTT. Thus we researched several physical characteristic parameters which might affect blood pressure (BP) with the standard that we can measure them easily and conveniently, chose valid physical characteristic parameters through a clinical testing and correlation analysis, and made the regression model using PTT and valid physical characteristic parameters for estimating unspecified peoples SBP. Comparing the result of the proposed method with American National Standards Institute of the Association of the Advancement of Medical Instrument (ANSI/AAMI), we know that the proposed regression model gives an acceptable result

A new blood pressure measurement using dual-cuffs

Most automatic sphygmomanometers use oscillometric method with a blood pressure cuff. Conventional oscillometric sphygmomanometer is simple to use and it needs no peripheral device. However, the method provides no guarantee of accuracy in all circumstance, because it is based on statistics. In this paper, we propose a new oscillometric method with two cuffs. A cuff is placed on upper arm as usual and another cuff is added on forearm. By adding one more blood pressure cuff, there are two different waveforms are shown and the different characteristics between both cuffs can be compared. The results of our experiments show that it is possible to measure blood pressure using dual-cuff oscillometric method.

Multifractal Analysis of Sleep EEG Dynamics in Humans

The aim of this study is to investigate the possibility that human sleep EEGs can be characterized by a multifractal spectrum using wavelet transform modulus maxima (WTMM). We used sleep EEGs taken from healthy subjects during the four stages of sleep and REM sleep. Our findings showed that the dynamics in human sleep EEGs could be adequately described by a set of scales and characterized by multifractals. We performed multivariate discriminate analysis to evaluate the use of multifractal features for classification. The multivariate discriminate analysis using within-groups covariance matrices for all sleep stages yielded a total error rate of 41.8%. In conclusion, multifractal formalism, based on the WTMM, appears to be a good tool for characterizing dynamics in sleep EEGs

An Efficient Adaptive Feedback cancellation using by Independent component analysis for hearing aids

In this paper, we proposed a feedback cancellation algorithm based on independent component analysis (ICA) for digital hearing aids. In conventional adaptive feedback cancelling systems, the normalized least mean squares (NLMS) algorithm used to reduce acoustic feedback in which hearing aids occurs, generally at high gains. But primary input signal depend on the acoustic feedback signal in higher-order statistics, proposed algorithm was better acoustic feedback cancelling performance than the conventional NLMS algorithm when the input signal has a Laplacian distribution with high-order processing in real-time simulation of TMS320C 6711 DSK

Vehicle Longitudinal Velocity Estimation on Inclined Road

Abstract : On-line and real-time information of the longitudinal velocity is the essential factor for the Advanced Vehicle Control Systems such as ABS(Anti-lock Brake System), TCS(Traction Control System), ESC(Electronic Stability Control) etc. However, the longitudinal velocity cannot be easily measured or calculated during braking maneuvering. A new algorithm is presented for the estimation of the longitudinal velocity with the measurements of the vehicle longitudinal/lateral acceleration, steering angle and yaw rate. The algorithm is designed utilizing the Extended Kalman Filter based on the 3 degree of freedom vehicle model. In order to compensate for the biased sensor signal on the inclined road, the inclined angle is also estimated. The performance of the proposed estimation algorithm is evaluated in field tests. Key words : Longitudinal velocity(종 속도), Inclined angle estimation(경사각 추정), Longitudinal acceleration compensation(종 가속도 보정), Extended kalman filter(확장된 칼만필터) Nomenclature

Notch filter design using theα-scaled sampling kernel and its application to power line noise removal from ECG signals

A new design approach is proposed for sharp notch FIR filters, whereby a modified alpha- scaled sampling kernel is utilized. In particular, the proposed approach provides closed-form formulae for filter coefficients, leading to an effective design procedure for sharp notch filters with given specifications. Simulation results demonstrate that the proposed design method yields high performance in removing the power line interference from ECG signals.

The localization and visualization of breast lesion in digitized mammogram

Sometimes the location of breast lesion in mammogram could make radiologists confused. In this paper, we present a method for computerized localization of breast lesion and its visualization using Cartesian coordinates and computer graphics.

Estimation of the climbing angle in the presence of yawing motion

The slope angle is one of the most influential factors which limit the control performance and the energy efficiency of not only internal-combustion engine vehicles but also electrified vehicles such as hybrid vehicles and plug-in hybrid electric vehicles. However, measuring the slope angle is not easy because slope sensors are not sufficiently accurate and they are too expensive to implement in vehicles. In this study, the climbing angle as well as the slope angle are considered in the presence of yawing motion on a sloping road, and both angles are estimated. In order to describe the combined vehicle motions when turning on a sloping road, a new three-dimensional dynamics model is proposed including the heading angle with respect to the road slope orientation. The extended Kalman filter is designed on the basis of the three-dimensional dynamics model on a sloping road, and the key parameters for the sloping road are updated using the geometry relationship. The proposed estimation method is evaluated using simulations and field tests with a hybrid electric vehicle.