Yutaka Hata

It is effective to measure cerebral surface and cerebral gyri for quantitative diagnosis hypoxic ischemic encephalopathy (HIE). The aim of this study is to propose a computer-aided diagnosis (CAD) system for infant with HIE using magnetic resonance (MR) images. The propose system automatically segments the whole brain from the MR images by using fuzzy active surface model, which can embed physicians' knowledge on the human brain into image segmentation system. The cerebral gyri are segmented by deforming user-given lines into cerebral sulci. The deformation is performed with fuzzy active contour model. The proposed CAD system was applied to 8 infants (3 weeks - 4 years 2 months old). The results showed that the system segmented the whole brain with high accuracy (sensitivity; 97.72 %, FPR; 0.31%), and the cerebral gyri were segmented well for all subjects.

The pivot shift test has been performed to assess the instability of the knee caused by ACL(anterior cruciate ligament) injuries. In previous reports, evaluations of the test have correlated with degrees of ACL injuries, and the test has been used for deciding treatment policy. However, the test depends on the clinician's subjective feeling. In this study, intelligent IMU sensors, which can measure time-series data of accelerations, angular velocities and earth magnetisms simultaneously, has been introduced into evaluating pivot shift test. The proposed method quantifies the pivot shift phenomenon as relative accelerations of the shank region by using time-frequency analysis. In the result of applying this method to the ACL injured subject, pivot shift phenomenon was detected correctly in comparison with video images taken simultaneously, the mean value of the maximum accelerations was 2.19±0.69m/s^2, and the correlation was indicated with grade values based on the clinician's subjective feeling.

心拍は、身体の変化を顕著に表す生体情報として知られており、自覚症状の現れにくい疾病を予防するためにも、その変化を継続的に観察することは重要である。さらに、心拍のゆらぎには、自律神経活動を推定する上で有用な情報も含まれており、一部の睡眠障害の要因でもある自律神経活動の変異を知る上でも有効な指標といえる。本稿では、この心拍を簡便かつ非侵襲に計測する技術を示す。実験により、本技術が心電と同等の計測精度を持ち、さらに、そのゆらぎから、自律神経活動を推定することができる可能性も確認した。

高齢者がベッドから降りる際の転倒事故は大怪我に至る可能性があり、転倒事故の予防はQOLの観点で重要な課題である。 事故予防のためには、高齢者が離床するタイミングを介護者が正確に把握できることが望ましい。本研究では、空気圧センサと超音波振動センサを用いた離床前動作の検出手法を構築した。本手法を健康な成人男性に適用した結果，正確に離床前動作を検出することを確認した。

It is very likely that the cerebral disease of infant leaves permanent brain disorder. The regions of disorder are different by a symptom, and brain is atrophied and deformed by degree of symptom. Therefore, it is effective for diagnosing such cerebral symptoms to measure the surface area of each gyrus. However, gyrus segmentation method for infantile brain is not yet established. This paper proposes the gyrus labeling method with fuzzy boundary optimization algorithm for infantile brain in magnetic resonance (MR) images. The proposed method was applied to 14 infantile subjects (3 weeks – 4 years 3 months old). The results showed that the cerebral gyri were successfully labeled with a mean sensitivity of 90.8% and a mean false positive rate of 0.1%.

Heart beat brings valuable information about human health condition. In these days,electrocardiograph has been considered the standard method of heart rate measurement. However, it is not suitable for daily healthcare because of its high cost and unease of use. In response to the problems,many studies of heart rate measurement have been done with considering unconsciousness and non-invasion. The authors have also researched and developed method and equipment of heart ratemeasurement by mainly using an air pressure sensor. The method employs fuzzy logic to extract heartbeat point from the sensory data. In this paper, the characteristics of fuzzy logic are discussed from theviewpoints of theoretical aspects with comparative studies. The experiments were conducted to provethat fuzzy logic is suitable for measuring heart rate with using air pressure sensor.

This paper describes an ultrasonic intestine thickness determination system for low anterior resection. At the operation of rectum cancer with a circular stapler, the intestine is pulled by the circular stapler. When the thickness becomes too thin, the corresponding cells necrotize. To solve this problem, it is necessary to measure the change of the thickness of the intestine. We propose a thickness determination method of the intestine with the ultrasonic probe of 15MHz. In our method, we determine the surface point by calculating the correlation coefficient between the surface echo and acquisition waveform. Next, we determine the bottom point by calculating three fuzzy degrees: amplitude of the bottom echo, correlation coefficient between the surface and bottom echo, and interval distance between the surface and bottom echo. Finally, we calculate the thickness between the surface and bottom points. As the result, we could measure the thickness within an error rate of 5.09%.

This paper proposes a functional assessment system of autonomic nervous system using an air pressure sensor. Heart rate variability is a recognized measure of autonomic nervous system. In general, heart rate variability is measured by an electrocardiograph. However, this method has to constrain human body to fix plural sensors directly in a surface of a body. The air pressure sensor can unconstraintly detect the vital information in bed by placing it to the under of the mattress. The proposal method detects heart rate variability with this system, and evaluates an autonomic nervous system. We employ a detection method of heartbeat point using fuzzy membership functions. The experimental results show that we detect RR intervals with the correlation coefficient of 0.851 with comparison to that of electrocardiograph. Then, the errors of the HF (index of parasympathetic system) and the LF/HF (index of sympathetic system) are 11.98% and 22.18%, respectively.

Horticultural therapy (HT) is gaining attention as a form of rehabilitations in medical fields especially such as occupational therapy and nursing care, although its effectiveness has not been proven yet. This paper uses a strictly medical point of view to assess whether or not HT is effective for improvement of functional activities in the brains of brain-damaged patients. Five patients in Ishikawa Hospital with cerebrovascular diseases were invited to participate in HT for a month in addition to their routine medication and physical therapy (PT). The HT program was designed by horticultural therapists. The original purpose of the HT program was to monitor its effects on mental healing, cognitive re-organization, and training of sensory-motor function. The Functional Independence Measure (FIM) and the Self-Rating Depression Scale (SDS) were performed before and after HT to assess the patients’ physical activities of daily living (ADL) and to determine the patients’ mental changes in depressive states, respectively. Functional magnetic resonance imaging (fMRI) during recognition tasks was also measured before and after HT. The ADL of all patients significantly improved after HT; however, the depressive states in all patients did not change remarkably after the HT. fMRI examinations showed that the visual area, the inferior temporal area, the fusiform gyros, and the supramarginal gyros (SMG), in addition to the motor area, the supplementary motor area (SMA), the sensory area, and the cerebellum were activated after HT. These findings suggest that HT can accelerate an improvement of activities in the “visual and color processing areas” and the “association areas” as well as the sensory-motor areas of the brain in the patients with cerebrovascular diseases. HT, therefore, stimulates parts of brain, that are not always evoked through routine physical rehabilitation. HT can complement the routine physical rehabilitation and help to improve damaged brain function. © 2008, TSI® Press Printed in the USA.

Many studies showed that the hemodynamic response (HR) to brief neural activity caused by the blood oxygen level-dependent effect is delayed some seconds, and that the HR latency (= time to peak from neural activation) varies among activation sites. This paper proposes a novel method for estimating HR latency by analyzing event-related functional magnetic resonance images based on a continuous wavelet transform. The proposed method can simultaneously detect activation areas and estimate the HR latency. We also studied variability of the HR latency across subjects within the same activation sites, across acquisition days within a subject, and among activation sites within a subject. The experiments were done on 10 healthy subjects with hand-gripping tasks. We found no significant difference of HR latencies at a given activation site within a subject across acquisition days. And, we found significant differences of HR latency between the supplementary motor area (SMA) and the primary motor cortex (M1) in individual subjects, and among subjects. © 2008, TSI® Press Printed in the USA.

Computer aided diagnosis (CAD) system is an effective system of systems engineering (SoSE) in the medical field. The CAD system using medical images is constructed by integrating medical image acquisition system, medical image processing system, and clinical data analysis system, and it presents both of quantitative and qualitative data for physicians. This article proposes a CAD system for diagnosing neonatal and infantile brain disorders. The CAD system acquires intracranial images using MR scanner system, and segments the cerebral volume and surface using medical image processing systems, and produces cerebral volume and area, and 3-D rendering of cerebral surface. Especially, this article proposes medical image processing systems based on expert knowledge systems for neonatal/infantile brain MR images. To validate the proposed CAD system, it has been applied to three neonatal and five infantile MR images.

This paper describes a fuzzy processing method for a respiratory rate monitoring system by an optical fiber sensor. This optical fiber sensor has a part of sensor sheet and a polarization detector. It noninvasively detects vital signal of human on the sheet by obtaining polarization variations. By using this sensor, we propose a fuzzy processing method of a respiratory rate for human in the bed. Our method was tested on five volunteers. We successfully detected a respiratory rate. In it, fuzzy logic plays a primary role in the detection. Our system determines fuzzy membership functions by using characteristic of respiration. Consequently, this system can noninvasively detect a respiratory rate by using a constraint-free device.

It is effective to measure the surface area of each gyrus for quantitative diagnosis of infantile brain diseases. This paper proposes an interactive gyrus labeling method for the infantile brain in magnetic resonance images. First, a user roughly gives guidelines of gyral boundaries on a 2-D projected image of the cerebral surface. The cerebral gyri are labeled by automatically determining gyral boundaries with respect to the user-given guidelines. The boundary deformation process is based on fuzzy rules. The automatically determined boundaries are validated by the user, and modified interactively. We applied the proposed method to 14 infantile subjects (3 weeks - 4 years 3 months old). The results showed that the cerebral gyri were successfully labeled with a mean sensitivity of 92.8% and a mean false positive rate of 0.1%. ©2008 IEEE.

Volumetric cerebrum and measurement of cerebral surface area using MR images plays a fundamental role in computer-aided diagnosis (CAD) of neonatal cerebral diseases such as hypoxic ischemic encephalopathy. There are many conventional methods for brain extraction from adult MR images. However, it is hard to apply these methods for neonatal MR images that image features are different from adult one. This paper proposes a novel method for extracting neonatal cerebral surface with sub-voxel accuracy using Thick Rubber Model (TRM). This method extracts a cerebral surface by deforming TRM so that pseudo MR images synthesized from TRM are identical to the given MR images. Experimental results showed that the proposed method extracted the cerebral surface with higher accuracy (mean RMS distance was 9.0 mm) in comparison with the conventional method (mean RMS distance was 15.7).

The aim of this paper is to assess whether horticultural therapy (HT) is effective for improvement of daily activity and brain functional activity in brain-damaged patients from a medical point of view. Five patients with cerebrovascular disorders were invited to participate in horticultural therapy for a month in Ishikawa Hospital. The Independence Scale in Activities of Daily Living (ISADL) and the Mini Mental State Examination (MMSE) were performed before and after a whole series of horticultural therapy program to assess a patient's activities of daily life and to determine the patient's cognitive function, respectively. Functional magnetic resonance imaging (fMRI) under recognition tasks were measured before and after the horticultural therapy. Independency of the daily activities and cognitive function tended to improve after the horticlutural therapy. fMRI examinations showed that the supramarginal gyrus (SMG), the motor area, the supplementary motor area (SMA), the sensory area, the visual area, the middle temporal gyrus, and the frontopolar area were activated after the therapy in most patients.

To diagnose total hip arthroplasty (THA) patients, it is important to analyze in-vivo kinematics of the implanted hip joint. There are some conventional analysis methods for estimating the pose/position of the implanted hip joint using 2-D/3-D image registration technique for 3-D multidetector raw CT (MDCT) images and 2-D X-ray radiograph images. One of the remained problems is that estimation results depend on the initial pose/position given manually. This paper proposes a fully automated method for estimating pose/position of the implants and the hip joint without giving initial pose/position. The proposed method releases us from manual interactions of giving initial pose/position by intervening between 3-D MDCT images and 2-D X-ray radiograph images with 3-D computer-aided design (CAD) model.

We propose an ultrasonic system to determine thickness and wave speed of an object. In it, we develop a triangle probe system composed of three probes; a central probe and two side probes. The central probe straightly transmits/receives ultrasonic waves, and the right probe receives ultrasonic waves transmitted from the left one. We move the triangle probe to depth direction of an object. Then, two peak intensities are revealed at the focal points of the surface and the bottom of the object. We employ fuzzy logic to extract the two focal points, and determine the wave speed and thickness of the object from these focal point data. The experimental results on two hard phantoms show that the method can successfully determine the wave speed and the thickness of the object with high accuracy.

In this paper, we propose a personal identification by sole pressure change. We obtain sole pressure change of multiple steps by using two pressure sensor sheets. Each pressure sensor sheet is inserted into each shoe as an inner sock. Then, we extract characteristics of sole pressure change from the obtained data. We make template data of both feet from the extracted characteristics. We propose a Euclidean distance based method for personal identification. As the experimental result, we have recognized one often volunteers with over 90% accuracy.

The pivot shift test has been performed to assess the instability of the knee caused by anterior cruciate ligament (ACL) injuries. However, the test depends on the clinician's subjective feeling. In this study, inertial and magnetic sensors have been introduced into quantitative evaluation of the pivot shift test. The analysis method extracts the knee movement of the pivot shift by using wavelet transformation. In the result of applying the proposed method to the ACL injured subject, pivot shift phenomenon was detected correctly in comparison with reference video images taken simultaneously. In the quantitative assessment, the mean of the maximum acceleration during the pivot shift was 2.19±O.69 m/s2 , and the maximum acceleration values were correlated with grade scores based on the examiner's subjective evaluation.

This paper describes a human health monitoring system by an air pressure sensor and an ultrasonic sensor system. The ultrasonic sensor system can obtain the state of a patient in bed by placing it under a bed frame. That is, we can determine whether or not a patient in the bed. The air pressure sensor system can detect heart beats by placing it to the mattress on the bed. By using two sensors complementary, we can detect the behavior before getting out of bed aided by fuzzy inference technique. The system of the two sensors can complementary detects the state, heart beat, a behavior before getting out of bed. Thus, the system of the two sensor systems can noninvasively and unconsciously provide human health information with high accuracy aided by fuzzy logic. © 2008 IEEE.

Estimating 3-D pose/position of knee implants in-vivo is one of important methods for evaluation of total knee arthroplasty (TKA). It has been performed with 2-D/3-D image registration of knee implants' 3-D geometrical model (i.e., CAD; computer-aided design) and 2-D X-ray radiography image, which can take a projection image of TKA implants in-vivo. Although they have been producing valuable results, they cannot be applied without 3-D geometrical models. It is the critical limitation for clinical situations because most of physicians cannot have 3-D geometrical model. This paper proposes a novel system for evaluating knee implants without 3-D CAD models, and it uses 3-D digital radiology (DR) images. The system is based on a new method, called fuzzy visual hull, which is an extension of the conventional visual hull by introducing fuzzy logic. The new method can reconstruct 3-D object shape from 2-D silhouette images with vague contour of objects. The new method was evaluated by using TKA implants in-vitro and computer synthesized images. The results showed that fuzzy visual hull has high robustness for noises independently added to silhouette images.

In this paper, a fuzzy identification method for cellular quantity of Bone Marrow Stromal Cells (BMSCs) in artificial culture bones is proposed. We attempt to identify for cellular quantity with an ultrasonic system and fuzzy inference approach. We employ two characteristics: the amplitude and the frequency; the amplitude is obtained from the raw ultrasonic wave, and the frequency is calculated from frequency spectrum obtained by applying cross-spectrum method. The experimental results show that the proposed method identifies cellular quantity in artificial culture bone with high accuracy. © 2008 IEEE.

In order to realize heart rate monitoring on a bed, there are mainly two types of approaches similar to other signal processing applications: frequency domain analysis and time-series domain analysis. In frequency domain analysis, FFT is widely used to extract heart rate from obtained signals. Since FFT assumes constant frequency, it cannot be used for extracting microscopic variability of heart rate. In time-series domain analysis, pattern matching based on autocorrelation is commonly used. The method is not only advanced in sensitivity to heart rate variability, but it is also sensitive to unexpected noise. In response to these problems, heart rate monitoring technology is proposed by using air pressure sensor. In this paper, a heart rate estimation algorithm employing fuzzy logic is proposed and effectiveness of fuzzy logic applied to biomedical sensing is discussed. The experiments were conducted to validate the effectiveness of the proposed technology by comparing it with other methods such as pattern matching based on autocorrelation. © 2008 IEEE.

We propose a thickness determination method of the intestine with the ultrasonic probe of 15MHz. We determine the surface point by calculating correlation coefficient between surface echo and an acquisition waveform. Next, we determine the bottom point by calculating amplitude of bottom echo, correlation with surface echo and bottom echo, and interval distance between surface echo and bottom echo. Finally, we calculate the thickness between the surface and the bottom points. As the result, we have obtained the thickness within an error rate of 5.09%. © 2008 IEEE.

To diagnose total hip arthroplasty (THA) patients, it is important to analyze in-vivo kinematics of the implanted hip joint. There are some conventional analysis methods for estimating the pose/position of the implanted hip joint using 2-D/3-D image registration technique for 3-D multidetector raw CT (MDCT). images and 2-D X-ray radiograph images. One of the remained problems is that estimation results depend on the initial pose/position given manually. This paper proposes a fully automated method for estimating pose/position of the implants and the hip joint without giving initial pose/position. The proposed method releases us from manual interactions of giving initial pose/position by intervening between 3-D MDCT images and 2-D X-ray radiograph images with 3-D computer-aided design (CAD) model.

This paper proposes a functional assessment system of autonomic nervous system using an air pressure sensor. The air pressure sensor can unconstraintly detect vital information by placing it under the mattress in bed. We perform functional assessment of autonomic nervous system by heart rate variability obtained by the system. In this system, we employ fuzzy membership functions with dynamic parameter to detect RR intervals. The experimental results show that we detect RR intervals with the correlation coefficient of 0.851 with comparison to that of electrocardiograph. Then the errors of the HF (index of parasympathetic system) and the LF/HF (index of sympathetic system) are 11.98% and 22.18%, respectively. © 2008 IEEE.

Recently, tracking algorithm has been actively researched to reconstruct 3D shape from video images. Currently, it is difficult to track a number of feature points although the various tracking algorithm based on gradient method or block matching, was proposed. In this report, we proposed an approach to track dense point set by Projective Voxel Space (PVS), and reconstruct 3D shape using the tracked points. Here, we automatically generate triangular meshes from the reconstructed dense point set, and represent 3D shape based on texture mapping. As a result, in comparison with conventional method, 3D shape is reconstructed with less missing parts. In some experiments, the validity of the proposed method is evaluated.

We describe a new ultrasonography system, which can identify an implant position in bone. Although conventional X-ray fluoroscopy can visualize implants, it has the serious disadvantage of X-ray exposure. Therefore, we developed a system for orthopedic surgery that involves no X-ray exposure. Barriers to the development of the system were overcome using an ultrasonic instrument and fuzzy logic techniques. We located distal transverse screw holes in an intramedullary nail during surgery for femur fracture. The screw hole positions are identified by calculating two fuzzy degrees of intensity and the variance. Results allow this system to identify the screw hole positions within an error of 1.43 mm, an error ratio adequate for clinical surgical practice. Copyright © 2007 The Institute of Electronics.

In this paper, we describe a new ultrasonic oscillosensor and its application in a biological information measurement system. This ultrasonic sensor has a cylindrical tank of 26 mm (diameter) × 20 mm (height) filled with water and an ultrasonic probe. It detects the vibration of the target object by obtaining echo signals reflected from the water surface. This sensor can noninvasively detect the vibration of a patient by placing it under a bed frame. We propose a recognition system for humans in bed. Using this sensor, we could determine whether or not a patient is in the bed. Moreover, we propose a heart rate monitoring system using this sensor. When our system was tested on four volunteers, we successfully detected a heart rate comparable to that in the case of using an electrocardiograph. Fuzzy logic plays a primary role in the recognition. Consequently, this system can noninvasively determine whether a patient is in the bed as well as their heart rate using a constraint-free and compact device. Copyright © 2007 The Institute of Electronics, Information and Communication Engineers.

Recently, 3 dimensional (3D) Reconstruction from camera images has been actively researched. In this report, we propose the technique for 3D reconstruction of polyhedral structure using a video camera with a light source. In this method, an object is shot from various viewpoints with illuminated by a light source of a camera. The normal to each plane of the component of an object is calculated from the illumination of object's surfaces. And the angle of camera pose is reconstructed by the factorization method. The polyhedral structure of an object is reconstructed by corresponding the angle of camera pose to the normal to each plane. Thus, the object's structure reconstruction is achieved by using only the series of video camera images. The validity of the proposed method is demonstrated through some experiments.

Eye movement is one of important index for sleep study. However, it is difficult to measure eye movement and brain function with functional magnetic resonance imaging simultaneously, for investigating the relationship between eye movement and brain function during sleep. We previously proposed a method to measure eye movement from video images that taken during sleeping. This method was based on estimating intensity profile by artificial neural network (ANN). However, this method requires manual detection of eye position from several infrared video images to train ANN. In this paper, we propose a method for estimating visual axes during eye closure. First, we define the visual axes from MR images to train ANN. Next, we estimate visual axes from given infrared video images by estimating intensity profile using the trained ANN. To demonstrate the performance of training the ANN method was applied to a subject. The experimental results showed that the proposed method can detect visual axes from given images with high accuracy.

It is pretty important to measure vital-sign continuously for keeping humans good health. There have been developed many equipments for vital-sign measurements. Among vital-signs, heart rates while asleep are focused on here because they will bring some information of humans' health condition. In this paper, an unconscious and non-invasive measurement technology is discussed to develop the equipment of heart rate measurement using simple and low-cost air pressure sensors. According to the experimental results, the technology is proven as to provide enough accuracy.

2-D/3-D image registration is a technique to estimate 3-D pose/position of 3-D model from 2-D image.It has been used in various fields including industrial and medical fields; especially, it has been applied foranalyzing knee joint kinematics. Roughly, matching score used in 2-D/3-D image registration can be classifiedinto two approaches: landmark based method and intensity based method. In case of landmark based method,the matching score is defined as a distance between landmarks in the images. Although the method is a simpleand high speed processing, the registration accuracy is depend on extraction accuracy of landmarks. Incontrast, in case of intensity based method, the matching score is defined as differences of intensity between theimages for all pixels. The method has an advantage that it is unnecessary to extract any landmarks, however, ithas a tendency toward the falling into local solutions. In this paper, we introduce attended/unattended ROI(region of interests) into matching score. By representing the ROIs with fuzzy spatial maps, we can decreasethe dependency of registration accuracy on defining ROIs. In addition, by employing ROIs, the proposedmethod improves the registration accuracy in comparison with intensity-based method. To validate theperformance of the proposed method, it has been applied to image matching between 3-D knee bone modelreconstructed from multidetector-row CT and 2-D digital radiographic image. The experimental resultsshowed that the proposed method estimated knee angles with a root mean squared error (RMSE) of 0.4 deg thatwas superior to conventional intensity-based method.

In these years, a composite of artificial culture bone and bone marrow stromal cells (BMSCs) are hoped to effective treatment to large bone defect as impossible to curing for natural healing. Conventional evaluation method for the cellular quantity is firstly to crush the artificial culture bone injected BMSCs. So, the approximate amount of cell for curing is unknown. Therefore, this paper describes an ultrasound evaluation system for cellular quantity of artificial culture bone. Our system firstly measures ultrasound wave into the composite. And, we obtain two characteristics values. One of these values, the amplitude value, is directly measured by obtained wave. Another the frequency value is calculated by frequency spectrum converted with cross-spectrum method. We employ fuzzy inference using correlation of these values and true quantity for the cellular quantity. As a result, our method is able to evaluate the quantity with high accuracy.

To diagnose the cerebral diseases using MR images, skull stripping is one of the fundamental image processing techniques. There are many conventional skull stripping methods for adult brain MR images. However, image features of infantile MR images are different from those of adult MR images, and in case of infant, the skull is close to the cerebral surface. Thus, these conventional methods for the adult brain cannot be applied to the infantile brains. In this study, we propose an automated method for stripping the skull region from infantile MR images. The proposed method is based on fuzzy rule-based active surface model (FASM) that has an ability of representing the physicians' knowledge with fuzzy IF-THEN rules. The experimental results of 8 infantile MR images validated that the proposed method extracted the cerebral region with a sensitivity of 98.84% and false-positive rate of 1.21%.

Transcranial ultrasonography can non invasively image the brain in real time processing. However, the ultrasonic wave causes refraction in the skull, so the conventional ultrasonography can not image the brain from arbitrary place. In this paper, we propose an imaging system by considering ultrasonic refraction. In this experiment, we use a cow scapula to imitate the skull and a biological phantom to imitate cerebral sulcus. To calculate the ultrasonic refraction, we require the scapula thickness. We can easily determine the echo from scapula surface. However, it is difficult to determine the echo from scapula bottom. In this paper, we calculate the scapula thickness by using fuzzy inference. In the inference, we employ amplitude, correlation coefficient and the elapsed time. As the result, our method can estimate the thickness of scapula at all point and can essfully visualize the phantom surface image from arbitrary places.

Recently, biometric personal identification is evolving in the field of security and personalized services. Personal identification based on walking pattern using load cell, camera and pressure sensor is human-friendly system. The pressure sensor in mat can obtain information, such as foot pressure and foot size. In this study we propose a personal identification method by pressure change in sole. In our method, we divide pressure change in sole for the features, such as peak pressure, timing of heel strikeand timing of toe push off. We consider two types of personal identification method: Euclidean distance based method and the other is neural network. As the result, the method of Euclidean distance could identify one of 10 subjects at 70% recognition ratio at 4 divisions The method of neural network could identify one of 10 subjects at 85% recognition ratio at 5 divisions.

This paper describes an ultrasonic registration system for locating screw hole positions of intramedullary nail. Currently, X-ray has been used for visualizing the nail into the femur. However, it has serious problem of X-ray exposure. We propose a locating method of the screw hole positions by doing a image registration. We perform an experiment by one-direction manual scanning using an ultrasonic array probe. In our method, first, we extract screw hole regions by calculating two fuzzy degrees: average of the intensity of eight neighborhood and variance of the intensity along long axis of the nail using fuzzy inference. Next, we do a registration between the obtained image with the exact image, where the exactimage is the truth image of the nail. The position of screw holes in the obtained image is calculated bymoving from coordinate of screw holes in the exact image using the translation matrix. As the result, we could locate the screw holes on center axis of the nail and calculate the center distance of two screw holes within an error of 1.0 mm.

In this paper, we propose a personal identification method using sole information. We employ pressure changes of sole in walking. First, we do a preliminary examination using a load distribution sensor. We employ a neural network for a personal identification method. As the result, we show a possibility of an identification system by sole information using the load distribution sensor. Based on the result, we propose a personal identification method by sole pressure changes using three air pressure sensors. This method could identify one of Ave volunteers at 85.4 % recognition rate. © 2007 IEEE.

Analyzing knee kinematics after total knee arthroplasty (TKA) has been attracting considerable attentions because the knee kinematics can be used to evaluate TKA patients and to evaluate TKA operations and design of knee implants. Knee kinematics can be estimated by 2-D/3-D image registration from 3-D computer-aided design (CAD) models of knee implants to 2-D X-ray image. Although there are many studies for estimating knee kinematics, they have common problems that are dependency on initial pose/position and falling into local maxima. This study proposes a robust 2-D/3-D image registration method based on evolutional computing. The evolutional computing has both characteristics of global search performance and of local search performance. The characteristics are suitable for solving the problems of 2-D/3-D image registration. The proposed system has been evaluated by applying it to computer-synthesized images, X-ray images of phantoms, and X-ray images of TKA patients. © 2007 IEEE.