小橋 昌司

新生児低酸素性脳虚血性脳の進行度合いの定量化に,脳容積や脳回表面積の測定は非常に有効である.本研究ではMR画像を用いた脳容積計測,脳回表面積計測が可能な計算機診断支援システムを提案する.本提案システムでは,全脳形状や画像特徴に関する知識に基づくファジィ動的モデルを用いて全脳領域を自動抽出する.また脳回分割においては,操作者が脳表上で描画した脳回境界線を基に,ファジィ動的モデルにより脳回境界を自動検出する.提案システムを修正齢3週間から4歳2ヶ月の被験者8名に適用した結果,Sensitivity 97.72%, FPR 0.31%で全脳領域の抽出が行えた.また全被験者に対し各脳回の表面積計測が行えた.

ACL(anterior cruciate ligament; 前十字靭帯)損傷により生じる膝の回旋不安定性の評価手法として,主にpivot shift testが用いられる.同検査方法は簡便でACL損傷の程度と相関があり,今後の治療方針の決定に有用な指標であるが,同検査法は検者の主観的評価に基づいており,客観性,定量性が低いという問題点を有する.本研究では,小型で高時間分解能な慣性センサを用いた非拘束膝回旋不安定性定量化システムを提案する.同提案システムは,pivot shift test時の大腿部,下腿部運動を計測した時系列データの周波数解析により大腿-下腿の相対加速度を求めることで,pivot shift test現象の定量化を行う.本システムをACL損傷例1例に対して適用した結果,同時撮影したビデオ画像との比較により,pivot shift現象を正しく検出できたことを確認した.また,pivot shift現象時の大腿部に対する下腿部の相対運動の最大加速度は2.19±0.69m/s^2であり,検者の主観的評価であるGrade値との相関も示唆された.

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.

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.

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.

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%.

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.

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 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 defects 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.

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.

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.

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).

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%.

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 of ten 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+/-0.69 m/s(2), and the maximum acceleration values were correlated with grade scores based on the examiner's subjective evaluation.

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.

本文は，空気圧センサシステムを用いた自律神経系機能評価を提案する．自律神経系は心拍変動によって機能評価することができる．心拍変動を検出する一般的な方法として，心電計を用いる方法がある．しかし，心電計は複数のセンサを体表に直接固定するために被験者を拘束してしまう．空気圧センサシステムは，ベッドのマットレスの下に置くことによって，生体情報を非拘束に感知することができる．本文ではファジィ推論を用いた心拍変動法を提案し，自律神経系機能評価を行った．7人の被験者に提案法を適用した結果，心拍変動を心電計との相関係数0.851で検出することができた．また交感神経系の指標となるLF/HFを22.18%の誤差率で，副交感神経系の指標となるHF(n.u.)を11.98%の誤差率で評価することができた．

近年,動画像から物体の3次元形状を復元するための追跡手法が盛んに研究されている.現在,勾配法やブロックマッチングに基づく様々な追跡手法が提案されているが,数多くの特徴点を正確に追跡する事は困難である.本報告では,射影ボクセル空間を用いる事で密な点集合を追跡し,それらを用いて3次元形状を復元する手法を提案する.ここでは,形状復元において,復元した密な点集合から自動的に三角網を生成し,テクスチャマッピングに基づいて形状を表現する.これにより,従来法に比べ物体の形状はより少ない欠落で復元される.実験により,提案法の有効性を評価する.

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.

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) x 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.

近年,カメラ画像処理による実物体3次元復元が盛んに研究されている.これまで画像中の照度情報から形状復元を行う "Shape from Shading",動画像の特徴点軌跡から特徴点の3次元位置を復元する因子分解法などが提案されている.本報告では光源付ビデオカメラを用いて多面構造をもつ対象を3次元復元する手法を提案する.提案法ではカメラに固定したライトの光を対象に照射して撮影を行う.そして,対象を異なる角度から撮影した動画像中の照度情報を用いて対象の面法線とカメラ視線方向を対応付ける.対象の面法線に対応するカメラ視線方向を因子分解法により復元したカメラ運動から推定することで対象の多面構造を復元する.これにより動画像のみから簡便に実物体の構造を実現する.実験を行い,その有効性を示す.

睡眠状態と眼球運動に強い関係があることはよく知られている.しかしながら,睡眠時において,脳活動の解析が可能な機能的MRIの撮影と同時に眼球運動を計測することは困難である.我々は以前,赤外線ビデオを用いた睡眠時における眼球運動計測方法を提案した.同方法は,ニューラルネットワークを用いて濃度プロファイルのモデル化を行うものである.しかしながら,ニューラルネットワークの学習データとして,赤外線ビデオから測定者が手動で眼球運動方向を計測しなければならず,非常に煩わしい作業であった.そこで,本研究では赤外線ビデオのあるフレームと同期した眼部MR画像を用いて閉眼時における視線を定義し,その視線角度を従来法のニューラルネットワークへの学習データとして用いる方法を提案する.提案法を覚醒閉眼状態の被験者に適応した結果,閉眼時においても赤外線ビデオから右眼0.89±2.91度,左眼1.10±3.60度の精度で視線角度推定が可能であることが確認できた.

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.

Pulmonary diseases of the lung often cause the change of elasticity. This article proposes a novel elasticity imaging method using multidetector-row CT (MDCT). The new method is based on non-rigid image registration from MDCT images of the inspiratory lung to those of the expiratory lung. The elasticity is calculated by local volume change between respirations. Also, this article introduces a new image registration method based on a fuzzy control system. The fuzzy control deforms the given image according to knowledge on density of lung vessels, shape, and anatomical structure. The proposed elasticity imaging method was evaluated using computer synthetic data and subjects’ data. The experimental results showed that the proposed method deformed the given image successfully, and estimated the relative elasticity with a correlation coefficient of 0.86. © 2007, TSI® Press Printed in the USA.

Rupture of anterior cruciate ligament (ACL) is a serious problem for playing sports, which causes in functional stability of the knee joint. To restore this problem, various operation techniques of ACL reconstruction are proposed. Thus, it is important to numerically characterize the knee kinematics after ACL reconstruction. Then, we proposed an analysis method to estimate the three-dimensional (3-D) knee kinematics. However, the estimation accuracy was not enough. Because the target image did not have high contrast, for example, at the boundary between the femoral bone and the tibial bone. Then, born regions can not be extracted preciously because the target image has low contrast. In this paper, we propose a fuzzy ROI (region of interests) based image registration. This method attend the region where has clear contour of bone region and ignore the region where has murky contour of bone region, by using fuzzy degree map which is assigned by the fuzzy region of interests (ROI).

Automated stripping of skulls from infantile brain MR Images is the fundamental work to visualize cerebral surface and to measure cerebral volumes. They are important to evaluate cerebral diseases because most cerebral diseases cause morphometric changes in cerebrum. This study proposes a novel image segmentation method based on fuzzy rule-based active surface model. The proposed method was validated by applying it to two neonatal (3W and 4W) and six infantile (SW to 4Y2M) subjects. The mean sensitivity was 98.84 %, and false positive rate was 1.21 %, and the cerebral surface was visualized well.

This paper introduces an ultrasound identification system for cellular quantity of artificial culture bone with fuzzy inference. In our method, first, we measure ultrasound wave. Second, we obtain the two characteristics of the amplitude and the frequency. The amplitude is calculated as the Peak to Peak value, and the frequency is calculated from frequency spectrum of transfer function by using cross-spectrum method. Our fuzzy inferences system estimates the cellular quantity from these values. As an experimental result, our identification system could evaluate the cellular quantity in culture bone with high accuracy.

In this paper, we describe medical ultrasonic systems, which evaluate a fine granule from a coarse granule. In ultrasonic systems, a measurement limitation is known as an object larger than the half-wavelength. However, we need to measure the object beyond the limitation. First, we describe an ultrasonic system for identifying a surface roughness. A fine granule evaluation model is made form the experiment. An ultrasonic system developed from the model can evaluate the roughness of a human imitated phantom with 89% accuracy. Second, we describe an ultrasonic system for identifying kinetic viscosity of liquid. The fine granule evaluation model is derived from a wave equation theoretically. The experimental results show that the developed system from the model can evaluate the viscosity.

Automated labeling of the cerebral gyri on the cerebral surface is a fundamental work for estimating the regional atrophy of the cerebrum. Estimating regional brain atrophy will help us to diagnose the cerebral diseases. This article proposes a fully automated method for labeling the cerebral gyri using 3-D human brain magnetic resonance (AM) images. The proposed method is composed of two steps; (1) initializing a surface model, and (2) deforming the surface model. They are based on,fuzzy pattern matching and fuzzy inference systems base on anatomical knowledge. This article also introduces a knowledge extraction system for constructing the systems. Comparison between the automatically labeled gyri and the manually labeled gyri showed that the automatically labeled gyri overlap with the manually labeled gyri well.

In this paper, we introduce a health monitoring system by both air pressure and ultrasonic sensors. The system of these sensors can complementary detect a behavior before getting out of bed with high accuracy aided by fuzzy membership functions. In this system, the ultrasonic sensor can obtain vibration information of human by setting it the under a bed frame. The air pressure sensor can also detect a pressure change of movement of human by setting it into the mattress on the bed. By using these sensors, we construct a fuzzy system to detect a behavior before getting out of bed.

Unconstrained patients health monitoring systems are required in the field of medicine and nursing, Our developed ultrasonic oscillosensor can detect the vibration of human vital by setting to the under of the bed. This paper proposes an extraction method of the heart rate by using this sensor. Our method extracts the weakly detected heart pulse by enveloping the obtained data. Since our method employs fuzzy membership functions, it can adapt to extract the heart rate for various heart frequencies. As the result, we were able to successfully extract the heart rate for four volunteers. Copyright - World Automation Congress (WAC) 2006.

Elasticity imaging is a new approach to diagnose the state of tissues in vivo. Almost all of elasticity imaging methods have been studied using ultrasound. However, such ultrasound systems can not be applied to the pulmonary tissues because the lung is fulfilled with air and almost power of ultrasound is reflected at the boundary of the lung. This paper proposes a novel tissue elasticity imaging method using multiderector computed tomography (MDCT). The present method estimates the elasticity based on image registration between the inspiratory MDCT images and the expiratory MDCT images of the same subject Use of the elasticity imaging for the lung will be a powerful tool for diagnosing the lung emphysema, the breast cancer or the other pulmonary diseases that cause the change of elasticity. Copyright - World Automation Congress (WAC) 2006,.

近年再生医療では親和性の高い人工培養骨と，骨芽細胞に分化する骨髄幹細胞(BMSCs)を組み合わせた混合物を骨補填剤として用いることが考えられている．しかしこの混合物内の細胞量を測定する方法は，BMSCsを注入した人工培養骨を粉砕し，電子顕微鏡を使用し目視で細胞を数えるのみであった．そのためこれらの混合物は測定以後臨床，研究に使用することができず，治療に最適な細胞量を知ることができなかった．そこで本研究では超音波装置を用いた人工培養骨内細胞量推定システムを提案する．本手法では上記の混合物に対して超音波を透過し，取得した波形から振幅と周波数の特徴値を得る．振幅値は取得波形から直接抽出し，周波数はクロススペクトル法により得られた伝達関数の周波数特性から算出する．これらの特徴値と従来法による真値の関係よりファジィ推論を構築し，細胞量を推定した結果高い成功率で推定を行うことができた．

現在，バイオメトリクス個人認証はセキュリティや個人サービスの分野で急速に発展している．ロードセルやカメラ，圧力センサなどを用いた歩行パターンによる個人認証は利用者の負担を減らすことのできる認証法である．特に，マット型の圧力センサは足のサイズや圧力分布などの多くの情報を得ることができる．本論文では，マット型圧力センサを用いた足底圧変化による個人認証を提案する．本手法では，圧力分布区域をいくつかの区間に分割し，それぞれの圧力が最大になる時間や踏み込み，踏み抜き時間のような特徴を用いて個人認証を行う．認証にはユークリッド距離と，ニューラルネットワークを用いる．結果より，ユークリッド距離を用いた認証では4分割で10人を70%の精度で認証を行うことができ，ニューラルネットワークによる認証では5分割で85%の精度で認証を行うことができた．