小橋 昌司

This paper describes a personal verification method based on fuzzy logic using dynamic sole pressure distribution while walking. The method employs a pair id sole pressure distribution change, and it is acquired by a mat type load distribution sensor. As a preliminary experiment for shoes, we take sole pressure data by bare foot and two kind of slippered foot. We extract thirty nine gait features from each sole pressure distribution change. We calculate a fuzzy degree of a feature from two fuzzy if-then rules and them fuzzy membership functions for a feature. These fuzzy membership functions are statistically determined by learning data. The fuzzy degree of acquisition sole pressure data is calculated by total of fuzzy degree of all features. The method verifies the walking person by using the fuzzy degree of the acquisition sole pressure data. When the fuzzy degree of acquisition data higher than a threshold, we verify the walking person as the target person. In our experiments, we employed 11 volunteers and took sole pressure data six times for each volunteer and foot situation. When the learning data included same kind of test data, we obtained low equal error rate. We obtained low false acceptance rate.

This paper proposes a body weight prediction method using autoregressive (AR) model and Fuzzy-AR model. First, we employ 6 persons body weight change data of 365 days. AR model predicts body weight of a day from these time-series data. We calculate an order of AR model for each person by Akaike's Information Criterion. In the experiment, we predicted body weight change of next day for those subjects. The AR model obtained 0.798 in correlation coefficient between predicted and truth values. Second, we propose a Fuzzy-AR model that predicts body weight of next p days from last p days, where p is the order of AR model. In this method, we propose a Fuzzy-AR model with the fuzzy membership function using last p days data. In the experiment, the Fuzzy-AR model obtained 0.558 in correlation coefficient on 2 subjects.

This paper describes a testicular tubules evaluation using 1.0MHz ultrasonic array probe. In this system, we evaluate a diameter of testicular tubules. We employ an ultrasonic array probe with the center frequency of 1.0MHz. We employ evaluation index that cumulative relative frequency of amplitude values. In the experiment, we employ 24 nylon lines as the testicular tubules. Amplitude of large nylon line echo is larger than that of small nylon echo. For the evaluation, we calculate cumulative relative frequency amplitude of acquisition data. Fuzzy if-then rules are made by the cumulative relative frequency of large and small lines. We evaluate a rate of large lines among all lines by using the fuzzy MIN-MAX center-of-gravity method. In this experiment, the proposed method successfully evaluated the rate of the large lines. We changed the rate of large lines in 24 nylon lines, and tested our method 20 times for each rate. We evaluated the rate with 5.77 % in mean absolute error.

Cerebral surface extraction from neonatalMR images is the basic work of quantifying the deformation of the cerebrum. Although there are many conventional methods of segmenting the cerebral region, only the rough area is given by counting the number of surface voxels in the segmented region. This article proposes a new method of extraction that is based on the particle method. The method introduces three kinds of particles that correspond to cerebrospinal fluid, gray matter, and white matter; it converts the brain MR images into the set of particles. The proposed method was applied to neonatal magnetic resonance images, and the experimental results showed that the cerebral contour was extracted with a root-mean-square-error of 0.51 mm compared with the ground truth contour given by a physician.

Home security in night is very important, and the system that watches a person's movements is useful in the security. This paper describes a classification system of adult, child and the other object from distance distribution measured by an infrared laser camera. This camera radiates near infrared waves and receives reflected ones. Then, it converts the time of flight into distance distribution. Our method consists of 4 steps. First, we do background subtraction and noise rejection in the distance distribution. Second, we do fuzzy clustering in the distance distribution, and form several clusters. Third, we extract features such as the height, thickness, aspect ratio, area ratio of the cluster. Then, we make fuzzy if-then rules from knowledge of adult, child and the other object so as to classify the cluster to one of adult, child and the other object. Here, we made the fuzzy membership function with respect to each features. Finally, we classify the clusters to one with the highest fuzzy degree among adult, child and the other object. In our experiment, we set up the camera in room and tested three cases. The method successfully classified them in real time processing.

Cerebral contour extraction from magnetic resonance (MR) images is a fundamental work to analyze brain MR images. The methods can be roughly classified into three approaches, voxel-based, mesh-based and particle-based. Each method has advantages and disadvantages. Especially, particle based method can extract the complicated sulci with sub-voxel accuracy. The remained work is to develop a method for estimating probability of particle transition among gray matter, white matter and cerebrospinal fluid. This paper proposes a new method for calculating the particle transition probability based on fuzzy inference technique. The proposed method was applied to computer synthesized MR images and neonatal brain MR images of volunteers.

About 80% of paediatric intractable epilepsy patients have accompanying cortical dysplasia. However, there are no established methods for noninvasive detection of cortical dysplasia. This paper proposes a novel method for automatically detecting cortical dysplasia using paediatric MR images. In order to evaluate cortical dysplasia in MR images, texture features and fractal dimension were extracted with an automated method and support vectors were used to evaluate the degree of cortical dysplasia. The proposed method was applied to three paediatric epilepsy patients. The automated method identified the cortical dysplasia lesion with a sensitivity of 94% a mean specificity of 85%, and a mean efficiency of 87%.

This paper describes a foot age estimation system using fuzzy logic. The method employs sole pressure distribution change data. The sole pressure data is acquired by a mat type load distribution sensor. The proposed method extracts step length, step center of sole pressure width, distance of single support period and time of double support period as gait features. The fuzzy degrees for young age, middle age and elderly groups are calculated from these gait features. The foot age of the walking person on the sensor is estimated by fuzzy MIN-MAX center of gravity method. In the experiment, the proposed method estimated subject ages with good correlation coefficient.

Implanted knee kinematic analysis plays one of important role in clinical and research fields of total knee arthroplasty. Although there are some studies to analyze X-ray images for estimating 3-D knee kinematics, most of them cannot analyze dynamic video because they strongly depend on manual interaction of giving initial pose/position. This paper utilizes particle filter for analyzing dynamic radiograph video of implanted knee. By using particle filter, the proposed method does not require not only user interaction but also computational iteration of parameter optimization. As the result, we shorten the computation time and improved the estimation accuracy. The estimation error was lower than 0.7 mm for rotation, and 0.5 mm for translation including out-plane, and the computation time was 1.27 sec per frame using a cluster computer.

This paper describes a trans-skull ultrasonic system that measures the blood flow velocity in brain under skull. In this system, we use an ultrasonic array probe with the center frequency of 1.0 MHz. The system determines the blood flow and locate blood vessel by Doppler effect. This Doppler effect is examined by the center of gravity shift in the frequency domain. We use three silicon tubes of different thickness imitated to blood vessel. We confirmed the change of frequency quantity of Doppler effect according to the water current velocity. The experimental result shows that the system detects the flow velocity by Doppler effect under skull and do automatic extracting method of water current.

This paper describes a biometric personal authentication method, using a pair of right and left sole pressure distribution changes, while walking. This system acquires sole pressure distribution changes via a mat type load distribution sensor, and does personal authentication. We employ twelve features based on the shape of a footprint, and twenty seven features based on weight movement for sole pressure data. Fuzzy if-then rules for each registered person are introduced, within which, their parameters are statistically determined in the learning process. We calculate the fuzzy degree of a pair of right and left sole pressure data for any registered person, and identify the walking person as the person with the highest fuzzy degree; the fuzzy degree being higher than a threshold. We employed 90 volunteers and authenticated them. We evaluate the proposed fuzzy method by five hold cross validation on which low false rejection and false acceptance rates are achieved. Thus, this fuzzy logic approach is precise for this biometric system. (C) 2011 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.

This paper proposes a biosignal detection algorithm aided by fuzzy logic for heart rate and respiration. We employ two kinds of sensors to evaluate the algorithm. One is a air mat sensor consisting of an air tube and a pressure detection device, and the other is an ultrasonic sensor consisting of an ultrasonic probe with 2MHz and water in a small tank. Both sensors detect biosignals of human in bed. This algorithm has dynamically updated parameters to adopt the variety in the biosignal amplitudes and periods of the individuals in fuzzy membership functions. In our experiments, we applied this to healthy male volunteers and evaluated the accuracies of detecting heart beat and respiration. As the results, the algorithm successfully detected the heart beat in the both sensor data and respiration number in the air mat sensor data. We compared them with truth values obtained by ECG or Respiration belt. In addition, we evaluated the accuracies of the dynamically updated parameters in the heart rate detection. Consequently, this algorithm detected both heart and respiration signals with high accuracies.

This paper describes a home care system for elderly by four detached multi-sensor network. The sensor network detects several bio-signals in bed. It consists of the following four sensors. An ultrasonic sensor detects human motion. An optical fiber sensor detects respiration. A mat-type sensor detects heart rate and respiration, and heart rate accesses autonomous nerve system. A microphone detects cough with phlegm to suction. The ultrasonic sensor attaches to bed frame, the mat sensor set under the bottom of the mattress in bed, the optical fiber is in mattress, and the microphone set in bed side. The sensor network can detect essential bio-signals such as heart rate, respiration, cough with phlegm to suction and body movement with high accuracy. © 2011 IEEE.

It is important to improve the quality of marine radar images because marine radar systems play a principle role of sea surveillance. However, it is difficult to recover signal strength decay with increasing distance, signals of behind objects and of shaded area. This paper proposes a new approach to improve radar image quality with system of systems (SoS) technology. The SoS is based on a ship-to-ship communication in which ships send and receive radar images, and the SoS constructs the high quality radar images using EM algorithm. Performance was validated using a computer simulation and using radar images acquired from a single radar system at multiple locations. The experimental results showed that the proposed method constructed high quality radar images, and recovered signal decay and signals of behind objects and of shaded area. © 2011 IEEE.

Measurement of cerebral volume and surface area using magnetic resonance (MR) image is effective for quantitative diagnosis of cerebral diseases. The measurement should require a brain segmentation process. Although many approaches for adult brain have been studied, there are few studies for neonatal brain. This study proposes a brain segmentation method for neonatal brain. Based on system of systems engineering technology, the proposed approach is composed from two systems; automated fuzzy logic based skull striping (AFSS) system and contour shape based modeling (CSM) system. AFSS segments the cerebral region based on Bayesian classification with Gaussian mixture model. CSM evaluates the skull stripping result of AFSS, and updates AFSS system parameters. Experimental results in 34 neonates (revised age between 2 weeks 1 day and 2 years 5 months) showed that the proposed approach segmented the brain region with sensitivity of 98.1% and false-positive rate of 27.9%. © 2011 IEEE.

This paper describes a biometric personal authentication method based on fuzzy logic using dynamics of sole pressure distribution while walking. The method employs a pair of right and left sole pressure data. These data are acquired by a mat type load distribution sensor. The proposed method has two processes. First, we calculate a fuzzy degree of each sole pressure data. In this process, we extract several gait features based on weight shift and shape of footprint. Fuzzy if- then rules for each registered person are introduced. In it, their parameters are statistically optimized in learning process. Second, we combine fuzzy degrees of right and left sole. In this process, we employ five operators. The method authenticates walking person with the combined fuzzy degree. We calculate the fuzzy degree of an interest person for all registered persons, and identify the interest person as the registered person with the highest fuzzy degree. While, we verify the interest person as the target person if the fuzzy degree of the interest person calculated for a target person is higher than a threshold. In an experiment on 50 volunteers, we obtained low false rejection and false acceptance rates.

This paper discusses a data analysis by YURAGI for a heart rate non-constraining monitoring system Three signals are employed: primary signal is obtained by a mat-type sensor, which is placed between a bed and subject, the second one is obtained by an ultrasonic vibration senor attached to bed frame, and third one is Gaussian noise. We compare the results from the synthesized data of the first and second signals with those of first signal and the noise. We employ weighted sum as the synthesized method. We consider Gaussian noise as YURAGI. The extraction algorithm was developed based on fuzzy logic. The comparison was done on 10 healthy volunteers and we evaluated the accuracy for various weight ratio. Here, we must concern the accuracy because the tiny accuracy difference causes large difference in the autonomic nerve system assessment. As the result, the results obtained from both synthesized signals were superior to that from mat-type sensor signal only. Thus, YURAGI analysis is useful to for detecting heart rate by mat-type sensor.

Loss of communication is a critical problem for advanced amyotrophic lateral sclerosis (ALS) patients. This loss of communication is mainly caused by severe dysarthria and disability of the dominant hand. However, reports show that about 50% of ALS patients have mild cognitive dysfunction, and there are a considerable number of case reports on Japanese ALS patients with agraphia. To clarify writing disabilities in non-demented ALS patients, eighteen non-demented ALS patients and 16 controls without neurological disorders were examined for frontal cognitive function and writing ability. To assess writing errors statistically, we scored them on their composition ability with the original writing error index (WEI). The ALS and control groups did not differ significantly with regard to age, years of education, or general cognitive level. Two patients could not write a letter because of disability of the dominant hand. The WEI and results of picture arrangement tests indicated significant impairment in the ALS patients. Auditory comprehension (Western Aphasia Battery; WAB IIC) and kanji dictation also showed mild impairment. Patients' writing errors consisted of both syntactic and letter-writing mistakes. Omission, substitution, displacement, and inappropriate placement of the phonic marks of kana were observed; these features have often been reported in Japanese patients with agraphia resulted from a frontal lobe lesion. The most frequent type of error was an omission of kana, the next most common was a missing subject. Writing errors might be a specific deficit for some non-demented ALS patients.

人工膝関節置換術（Total knee arthroplasty:TKA）後の膝関節の動態解析は，TKA術後膝の診断や，TKA術に関する研究開発において主要な役割を示す．これまでの研究において2次元のX線透視画像と人工膝関節の3次元形状モデルを用いた2-D/3-Dイメージマッチング手法が多く提案されているが，これらは静止画像による解析に留まり，膝関節の連続的な動作を動画像により解析する研究はほとんど行われていない．本論文では，モンテカルロ法を用いた人工膝関節の3次元動態解析システムを提案する．提案手法は複数の候補を作成するパラメータ探索による2-D/3-Dイメージマッチングを用いて人工膝関節の3次元位置姿勢を推定する．これにより動画像の連続フレーム解析を可能とする．実験の結果，提案手法により膝関節の連続的な動作の解析，膝関節角度の推定が可能となり，7例の被験者に対する適用結果よりいくつかの膝関節動態のパターンを観察できた．

There are few studies on computer-aided diagnosis (CAD) system for neonatal magnetic resonance (MR) images. In addition, because it is difficult to apply multiple examinations for neonate, we should maximize data which are derived from a set of MR images. Under these requirements, this paper introduces system of systems (SoS) framework into analysis of neonatal MR images. The present system called SoS-CAD for neonatal brain is composed from skull stripping system, brain shape homologous modeling system, gyral labeling system and cerebral contour extraction system. By collaborating the systems with each other, the SoS-CAD produces multiple numerical and geometrical data from a set of MR images. © 2010 IEEE.

This paper describes a method for a heartbeat and respiratory rate monitoring system using air pressure sensors and ultrasonic oscillosensor. By using these sensors, we propose a detection method of the state of human and an extraction method of heartbeat and respiratory rate in bed by fuzzy logic. Our method was examined on four healthy volunteers. We successfully detected the state of human and extracted heartbeat and respiratory signals. In our method, fuzzy logic plays a primary role in the detection of the state and extraction of heartbeat and respiratory signals. An experiment on four healthy volunteers was done. Consequently, our proposed method noninvasively and successfully detects the state of human and extracted heartbeat and respiratory rate in the bed by using the unconstrained sensors.

For estimating 3-D pose position of artificial knee implants in vivo, there are some studies based on 2-D/3-D image registration of 2-D fluoroscopy images and 3-D geometrical model. Knee implant mainly consists of femoral component and tibial component. Most conventional studies estimate 3-D pose position of femoral component and tibial component individually. Rather, they don't evaluate relative position between the femoral and tibial components. This paper proposes a method for estimating 3-D pose position of implanted knee based on particle filter. A priori knowledge on the relational position of the components are utilized by using fuzzy membership functions. The experimental results for a patient and simulation DR images showed that the proposed method adequately estimate 3-D pose position of the femoral and tibial components with respect to relational position between the components.

This paper proposes a biometric personal authentication method based on one step foot pressure distribution change. We acquire the foot pressure distribution change by mat type load distribution sensor and use it as a personal authentication. We employ twelve features based on shape of footprint, and twenty seven features based on movement of weight while walking. A classifier for each feature is developed on the basis of fuzzy inference. The classifier is trained by a clonal selection algorithm in artificial immune system. A personal authentication system for one step is made every classifier for all features. We employed 10 volunteers, and we took the step data five times. We evaluated our method by five-fold cross validation method. We obtained low false rejection and acceptance rates in identification and verification.

Automated morphometric analysis using human brain magnetic resonance (MR) images is an effective approach to investigate the morphological changes of the brain. However, even though many methods for adult brain have been studied, there are few studies for infantile brain. Same as the adult brain, it is effective to measure cerebral surface and for quantitative diagnosis of neonatal and infantile brain diseases. This article proposes a skull stripping method that can be applied to the neonatal and infantile brain. The proposed method can be applied to both of T1 weighted and T2 weighted MR images. First, the proposed method estimates intensity distribution of white matter, gray matter, cerebrospinal fluid, fat, and others using a priori knowledge based Bayesian classification with Gaussian mixture model. The priori knowledge is embedded by representing them with fuzzy membership functions. Second, the proposed method optimizes the whole brain by using fuzzy active surface model, which evaluates the deforming model with fuzzy rules. The proposed method was applied to 26 neonatal and infantile subjects between -4 weeks and 4 years 1 month old. The results showed that the proposed method stripped skull well from any neonatal and infantile MR images.

Analyzing knee kinematics of implanted knee after Total Knee Arthroplasty (TKA) is affective approach in the research area of orthopaedics. There are some studies based on 2-D/3-D image registration of 2-D fluoroscopy images and 3-D geometric model. However, these conventional studies are designed for still statics image analysis, and there are a few studies for dynamic image of continuously knee movement. In addition, the another problem are to fall into local maxima in high-dimensional search space, and not to consider continuous knee movement. This paper proposes an analysis method of the continuous implanted knee kinematics based on Particle Filter. The proposed method estimates 3-D pose position of the implanted knee joint using 2-D/3-D image registration based on Particle filter. Particle filter is able to estimate optimal solution from multiple candidate pose position. The experimental results showed that the proposed method analyzed the continuous movement of the knee joint and estimated the knee joint angles. © 2010 TSI Press.

This paper propose a biometric personal identification method based on a pair of right and left sole pressure distribution change. We acquire the sole pressure distribution change by load distribution sensor and use it for a personal identification. We employ twelve features based on shape of footprint, and twenty seven features based on movement of weight during walking for each sole pressure data. We make these fuzzy if-then rules. We calculate a fuzzy degree of a pair of right and left sole pressure data for one person, and identify person by this fuzzy degree. We evaluated our method by five-hold cross validation method. The low false rejection and acceptance rates are evaluated from 20 to 90 persons. © 2010 TSI Press.

Conventional eye gaze tracking are based on special contact, optical equipment, Electrooculogram, etc. Although they have been produced valuable results in many areas, they cannot obtain the absolute eye gaze but obtain relative one based on calibration. This study proposes a method for detecting absolute eye gaze using MR images. Because MR images can obtain the sectional images of the eye ball, the method needs no calibration. The proposed method detects the eye gaze by segmenting the Vitreous, and lens of the eye ball. The method was applied to healthy subjects successfully. The estimated results were validated by comparing with the conventional method based on optical equipment.

Anterior cruciate ligament (ACL) injury and knee osteoarthritis are well-known injuries of the knee joint, and pivot shift is a symptom of the ACL injury. Today, to diagnose the pivot shift phenomenon, the manual testing is examined for the early diagnosis, however, it should be affected by inter- and intra observer variability. This article proposes a novel system for detecting and quantifying the pivot shift phenomenon during pivot-shift testing using inertial and magnetic composite micro electro mechanical systems (MEMS) sensor. The system estimated 3-D acceleration vector caused by the pivot shift phenomenon using wavelet transform. The experimental results indicated that the pivot shift phenomenon was detected and quantified. And, there are correlation between the maximum acceleration of the knee movement at the pivot shift and the conventional evaluation by assessors. © 2010 IEEE.

The estimation system of the knee joint angle that decreases the variability caused by the subjective diagnosis of the knee joint disorders has been attracting a considerable attention. This paper proposes an unconstraint knee joint angle measurement system using inertial and magnetic composite MEMS sensor. The proposed system estimated the posture difference between the thigh and shank region from the difference of the measurement vector between the compound sensors attached on the shank and the thigh, respectively, and 3-D knee joint angles can be calculated by applying Grood's definition. Through experimented results, the knee flexion angle was obtained compared with the true value due to the measurement error of 1.3 deg in average. © 2010 IEEE.

Cortical dysplasia is a congenital anomaly of cerebral cortex. It accompanies considerable number of pediatric intractable epilepsy patients. Therefore, it is very effective to detect cortical dysplasia lesions and to estimate dysplasia degree quantitatively in pediatric brain MR images for planning treatment. However, image features on the pediatric brain MR images of cortical dysplasia aren't clarified. This paper proposed the estimation method using intensity profile by detecting cortical dysplasia in pediatric brain MR images. The experimental results for three subjects with cortical dysplasia showed that the proposed method detected cortical dysplasia lesions with a mean sensitivity of 90.9%, a mean specificity of 93.1%, and a mean efficiency of 92.0%. © 2010 TSI Press.

Brain shape is deformed regionally by kinds of cerebral diseases and the degree of progress. Therefore quantitative evaluation of the deformation using MR images is effective for diagnosis of cerebral diseases. We proposed a homologous brain shape modeling deformation for quantitative evaluation of the brain shape using sulcal-distribution index (SDI) in MR images. So in this paper, we propose the homologous brain shape modeling. And we find the availability of the homologous brain shape modeling by investigating relationship between the movement distance with the homologous brain shape modeling and gray matter (GM) density of voxel based morphometry (VBM). This study employed nine male and two female and investigate a difference between male group and female group. The experimental results showed that the relationship between the homologous brain shape modeling and VBM was found from the same detection significant difference. © 2010 TSI Press.

In functional test of hip joint, anatomical coordinate system is used. Anatomical coordinate systems are defined by inputting landmarks manually. Therefore decision of anatomical coordinate systems includes inter- and intra-operator variability. In addition, variability of anatomical coordinate systems will affect results of diagnosis and/or cause critical error of total hip arthroplasty (THA) is operation that replaces damaged hip joint by implants. This paper proposes automated definition of anatomical coordinate systems and evaluation method for clinical study. As a result of having applied proposed method, anatomical coordinate system was decided automatically. A result of comparing with pelvic coordinate systems was decided by orthopaedic doctors, an angle mean error ± standard deviation (SD) was 0.78 ± 0.34 deg and an position mean error ± SD was 2.6 ± 1.6 mm. As a result of having calculated pelvic tilt and symmetry of pelvis, the proposed method obtained useful data. © 2010 TSI Press.

Quantitative diagnosis of the knee joint dynamics is required to decrease the inner-and intra-observer variability. This paper proposes a noninvasive, unconstrained and free field of measurement system of 3 degree-of-freedom knee joint angles. The proposed system employs a compound sensor of inertial and magnetic sensors. Based on a rigid-body link model, the proposed method enables a measurement system. The experimental results showed that the proposed method estimated the flexion of knee joint angle with a mean displacement of 1.3 deg.

It is effective to evaluate magnetic resonance (MR) images for diagnosing neonatal cerebral disorders because they often accompany the deformation of the brain shape. However, there are many difficulties when radiologists manually extract cerebral surface from the MR images. Therefore, it requires to extract the cerebral surface from neonatal MR images automatically. There are many methods to extract cerebral surface from adult MR images, but there are few methods for neonatal MR images. This paper proposes a new extraction method based on particle method. The proposed method introduces three kinds of particles corresponding to cerebrospinal fluid, gray matter and white matter. First, particles are assigned according to the cerebral shape. Second, particles are moved to form the homogeneous particles, and are transited to the other particles with respect to MR signal. The proposed method was applied to neonatal MR images. The results showed that the proposed method extracted cerebral surface with high accuracy.

In this paper, we analyze human gait pattern and estimate her/his foot age. We acquire foot pressure distribution change as gait pattern by a mat type load distribution sensor. From the foot pressure distribution data, duration of gait cycle and center of foot pressure (CFP) changes are determined for each stride. We employ four estimation indexes such as step length, step CFP width, the time of double supporting period and distance of step CFP changes. We employ 87 volunteers, and divided them to young, middle age and elderly groups. By comparing of three groups, we found that elderly had shorter step length and larger step CFP width than young and middle age people. Besides, the double supporting time of the elderly was longer, and distance of step CFP changes was longer than those of young and middle age people. From these facts, sixteen fuzzy IF-THEN rules are made. We determine a fuzzy degree for her/his foot age by fuzzy MIN-MAX center-of-gravity method. In our experiment on 87 volunteers, we compared these results with regression method.

This paper describes a trans-skull ultrasonic system that measures the blood flow velocity through the brain's blood vessel under skull. In this system, we use an ultrasonic array probe with the center frequency of 1.0MHz. The system determines the blood flow by Doppler effect. This Doppler effect is examined by the center of gravity shift in the frequency domain. We test the system in the condition of the water flow in silicon tube under the cow scapula. The experimental result shows that the system detects the flow velocity by Doppler effect and confirms the usefulness of the method under skull.

This paper describes a method for distribution of people monitoring system using a 3D camera. This camera measures distance and intensity distribution based on time of flight (TOF). From the obtained distance data, we perform clustering processing to detect the distribution of people. In our method, fuzzy logic plays a primary role to decide the cluster, i.e., people number. Our proposed method applied for 120 sec in a room. We successfully detected distribution of people in a room for moving 3 people distribution. Consequently, our proposed method successfully detected distribution of people using automated cluster number determination. © 2010 TSI Press.

Voxel based morphometry (VBM) is an approach which detects voxels whose brain tissue density is statistically different from control groups in magnetic resonance (MR) images. It has been applied to diagnose cerebral disorders, cognitive dementias, etc. However, VBM is not applied to neonatal brains because of large differences between the adult brain and the neonatal brain. This article proposes a modified VBM for neonatal brain. The modified VBM segments the brain region by using skull stripping method for neonates, and normalizes the segmented brain into the standard neonatal brain. The standard neonatal brain is constructed by using non-rigid image registration. The proposed method was applied to 14 neonates whose age was between -1 month and 1 month. For any neonates, the method normalized the brain shape successfully.

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, the mean of the maximum accelerations of the pivot shift was 2.19±O.69 m/s2, and the maximum accelerations were correlated with grade scores based on the clinician's subjective feeling. © 2010 TSI Press.

Precise measurement of cerebral surface area will explores a new method for evaluating cerebral disorders because the cerebrum will be deformed by the cerebral disorders. Conventional methods for segmenting the cerebral region from MR images give coarse area by counting the number of the surface voxels of the segmented region. In contrast, this paper proposes a novel method for extracting cerebral contour with sub-voxel accuracy. The new method is based on particle method, and introduces three kinds of particles that are correspond to cerebrospinal fluid, gray matter and white matter. The proposed method was applied to neonatal MR images, and the experimental results validated that the cerebral contour was extracted with a root-mean-squared-error of 0.45 mm in comparison with the ground truth contour given by a physician.

This paper describes a fuzzy segmentation approach and the rendering technique called fuzzy maximum intensity projection (FMIP) for the endorrhachis in magnetic resonance images. First, we propose a fuzzy segmentation procedure, which assigns the high fuzzy degree for the high possibility to the endorrhachis. Second, we describe FMIP, which projects higher fuzzy membership degrees to brighter values in the 2D plane for every voxel in the volume dataset. This enables us to visualize regions of interest with higher accuracy after the fuzzy segmentation is done in the dataset. The applicability of them is tested in the visualization of the endorrhachis in magnetic resonance images. A comparison between FMIP and MIP shows that FMIP visualizes it more effectively. (C) 2009 Elsevier B. V. All rights reserved.

In this paper, we describe a human health management system scheme and its practical applications. Specifically, it focuses on health management, medical diagnosis, and surgical support system of systems engineering (SoSE). The application domains discussed here are broad and essential in health management and clinical practice. Firstly, we describe a system of systems (SoS) in human health management. Within it, a notion of health management is introduced and discussed from the viewpoint of SoS. Human health management is the first level of daily monitoring for a healthy human. Sensing and control technology during sleep are espectially focused on because the quality and quantity of sleep has considerable impact on health. Secondly, an SoS in medical diagnostic imaging is discussed. This section introduces a clinical usage of a magnetic resonance imaging (MRI) scanner for the diagnosis of certain diseases. In it, there is a new system that consists of image processing system and expert medical knowledge system described by fuzzy logic. To demonstrate the effectiveness of the new system, applications to human brain magnetic resonance images and orthopedic kinematic analyses are introduced. Thirdly, we describe an SoS in medical ultrasonic surgery support device. This section introduces a novel ultrasonic support system for supporting crash bone orthopedic surgery.

In this paper, we propose a trans-skull imaging system of the human brain using an ultrasonic array probe. In it, we employ a cow scapula imitated to human skull and a steel with ditches imitated to cerebral sulci. We scan the phantom consisting of the bone and steel ditches by a 32channel array probe and obtain the B-mode image. From the B-mode image, we extracted the bone thickness by fuzzy inference, and visualize the ditches by filtering techniques. Experimental result shows that the mean error of bone thickness is less than 1mm and that the mean errors of the ditch width and depth are 6.9mm and 2.8mm, respectively.

This paper proposes functional assessment system of autonomic nervous system by the heart rate variability using an air cushion sensor. The air cushion sensor can unconstraintly detect vital information by sitting down on the sensor. We perform functional assessment of autonomic nervous system by heart rate variability obtained by the system. We built the real time display system for visualizing the autonomic nervous system functions. 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 0.846 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 18.34% and 16.99%, respectively.

This paper describes a system of systems for heath care of elderly. The system consists of three systems: one is the system that detects heart rate and it provides the condition of autonomous nerve system. The second one is the system detecting respiration. Third one is the system detecting cough with phlegm to suction. In them we emply non-contacted three senors such as an ultrasonic oscillosensor touched to bed frame, an air pressure with an air tube in matress in bed and PCM Recorder with microphone. The system of systems can detect fundamental biosiganls of heart rate, respiration and cough with phlegm to suction, and it provides the condition of primary biosignal of heart and respiration as well as autonomous nerve system.

The brain shape is deformed regionally by kinds of cerebral diseases and the degree of progress. Therefore quantitative evaluation of the deformation using MR images is effective for diagnosis of cerebral diseases. To evaluate the cerebral deformation, almost conventional methods are based on normalization of the brain shape which deforms the evaluating brain into the standardized brain. Because the normalization process does not take into account anatomical features such as the cerebral sulci and gyri, in some cases the normalization process produces that one sulcus of the evaluating brain miss-corresponds to the other sulcus of the standardized brain. This paper proposes a homologous brain shape modeling method for quantitative evaluation of the brain shape in MR images. We define a new image feature called sulcal-distribution index (SDI) to represent the 3-D distribution of sulci, and the proposed method deforms a template brain model so that SDI of the deformed brain model calculated from the evaluating brain MR images is similar to SDI of the template brain model. By using SDI, the proposed method can take into account anatomical features of the cerebral sulci. The experimental results showed that the proposed method homologically modeled the brain shape with a mean displacement of 1.3 mm.