We suppose a practical method to measure degree of arteriosclerosis noninvasively. This method is based on visualization of 2-dimensional velocity using time series echograms recorded by high-frame-rate echography. Recording cross section of artery, the motion of it seems to expand and contract concentrically. The expanding and contracting velocity consists of both elastic component and surging component. To elucidate only elastic component, we expanded this method to detect an elastic index which is defined as ASR (Arterial Strain Rate). ASR is able to induce an elastic index of artery. Applying ASR to rubber tubes, elasticity can be classified easily. So we applied to human common carotid arteries (104 subjects) whose age ranged from 13 to 83 years old. Elastic index calculated from ASR ranges about 1.0×10^-4Pa^-1 under 30 years old, but it decreases in proportion to aging which ranges about 0.2×10^-4Pa^-1 over 70 years old. These results indicate that artery motion is reduced with aging. This method has a possibility to be used to estimate degree of arteriosclerosis.

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Spiral wave activity and its breakup in excitable media have been considered as possible mechanisms for tachycardia and its transition to fibrillation. However, the mechanism of breakup has not yet been clarified. Here, we have examined the effects of spatial inhomogeneity of heart muscles as one possible factor for the breakup, using computer simulations of two dimensional FHN model with 100×100 cells configuration. Inhomogeneities are introduced as the variances of the refractory period and/or the coupling constant which corresponds to the conduction velocity from cell to cell or from block to block. It is found that, contrary to precedent reports, how large the variance is, cell to cell inhomogeneity does not break up spiral waves. The variance must be from block to block and the minimum size of the block for the breakup depends on the size of spiral waves. The effects of parameter changes in all or in part and those of additional stimulations were also examined. Besides of breakup, we could observe phenomena corresponding to anchoring (pinning) and hot spot. Secondly, we have studied the interactions of spiral waves. It was said that if once several (3-6) spiral waves exist simultaneously, although some of them may disappear by collisions, some may be broken up through their interactions and the resultant number of spiral waves does not change so remarkably. They said this might correspond to and must be sufficient condition for lasting fibrillation. To investigate this possibility, we devised a new method by analysing FHN model properties, which can generates multiple spiral waves with any direction of rotation at any place in the media. Using this method, we embeded six spiral waves in two dimensional media and examined their interactions. Simulation results showed no breakup and we could not approve the above hypothesis.

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The electrocardiogram consists of the cardiac electric phenomena, the body morphology and the conductivity distribution in the body. In the conventional electrocardiogram inverse study, to localize the stimulus in the heart, all of them is needed. However, getting them non-invasively, especially, the conductivity distribution is difficult. The purpose of this paper is to acquire information independent of the conductivity in the body, but related to the occurrence and the propagation of the stimulus in the myocardium itself, from the electrocardiogram. This paper proposed an evaluation method for extracting the Rate of Area Variation with Time (RAVT). The method we proposed for extracting RAVT, takes the inner-product between the potential distribution and its derivative with time on the body. Two kinds of electrocardiogram are used for the extraction, a potential map and its time derivative. The time derivative map on the body reflects the dynamic information, or the stimulus movement, and shows a propagation form, which consists of the area variation, the direction variation and the position variation of the stimulus. RAVT was analyzed by computer simulation with a model of the moving bipolar current source as the stimulus settled in an ellipsoidal cylinder. From the measured body surface potential maps (BSPM) of a normal human and a inferior myocardial infarcted case, RAVT was also extracted. It has been found that RAVT corresponds to the phenomena of the electric activity of the myocardium qualitatively, and reflects one of the heart functions, in the respect of the stimulus area variation.

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In functional MRI (fMRI) examinations using Echo-planar Imaging (EPI) sequences, brain displacement in the reconstructed images occurs due to physiological motion artifacts and static magnetic field drift. We have developed a new reordering technique to correct for such displacement. This reordering technique is based on the principle that the displacement can be reduced when using an EPI sequence by removing first-order phase shift along the k-space axes; that is, by using a phase-mapping technique. We applied the reordering technique to an fMRI data set to confirm its effectiveness. The fMRI data set was acquired with a 1.5-T MRI system (MRH1500AD, Hitachi Medial Corporation) using a multislice interleaved EPI sequence (4 slices, 8 shots per slice, FOV=240×240mm, slice thickness 6mm, matrix size=128×128, TR/TE=1250/10ms, FA=60°). We used the first image of each slice as the reference image. The inclination angles along the k-space axes were calculated with the least-squares method. The signal-to-noise ratio will affect the precision of the inclination angles, so we tried to optimize the data-selection parameters by varying the number of data points from the origin in k-space (±10 to 30 points), and by varying the threshold value (1% to 5% of the signal intensity of the origin in k-space). After correcting for displacement, we made error images of each imaging plane to estimate the accuracy of the selection methods. All error images before the correction had high error value regions. We compared the error values in the regions for various parameter values and found that setting the threshold value at 1% could achieve the most accurate correction. We conclude that this reordering technique using phase maps can be used to accurately correct an fMRI data set taken from an EPI sequence.

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Operative procedures for sites invisible to the naked eye require three-dimensional (3-D) monitoring. This is superior to 2-D monitoring in the respect that the access of the surgical tool to the surgical site has to be accurate. The 3-D endoscope we developed has a straight stainless steel shaft with a 2.7mm external diameter. It consists of a single channel with one object microlense at the tip, relay microlenses installed in the shaft, and light-guide optical fibers inserted in the shaft. Natural color views are shown on a 17 inch CRT with a real-time signal processor through a three CCDs camera. The signal processor creates other views by shifting the original views appropriate distances. Two separate views are displayed alternately at 120Hz, and surgeons can see these three dimensional visions by wearing light-weight eyeglasses with a liquid crystal shutter driven remotely by infrared signals synchronized with the signal processor. This system was applied to monitor surgical sites during pulmonary thromboendarterectomy. The newly developed 3-D rigid endoscope could be inserted into the pulmonary artery, even in areas invisible to the surgeon's naked eye without interfering the surgeon's visual field. The assistants and nurses could thus see the fine surgical procedure through three dimensional vision, and the vasculature of the pulmonary artery could be examined even after the procedure. This rigid endoscope has the smallest diameter to date. This system is useful for visualizing surgical sites in cardiovascular surgery in which the operative field is not widely denuded.

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We have developed an on-line Japanese character entry system with handwriting input device for visually disabled persons (particularly, acquired blind persons). This system is composed of an electric tablet for writing a character, a hand controller for controlling the system condition, a recognition algorithm of handwritten characters and a voice synthesizer which indicates a recognized character. For characters written by visually disabled person, we already proposed a character recognition method based on the relative direction between two strokes (RDS method). The RDS method is available for characters which have many strokes. However, as the feature parameters of the RDS method are decreasing for the characters having less than 6 strokes, recognition errors are increasing. This paper investigated the improvement (fusion) method which is added the new LSDS method (the method is based on the line segment directions in a stroke) to the RDS method. From the experimental results, it is shown that the satisfactory recognition accuracy and efficiency can be obtained using this newly recognition method in the classification of Japanese characters written by visually disabled persons.

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Awake background EEG represents the fundamental, spontaneous brain activities, and therefore it serves as one of the most important parameters for the EEG interpretation. Specially, characteristics of slow waves of δ and θ frequency range play an important role in the electroencephalographer's visual inspection as an index to show the degree of abnormality of brain function. In this paper, the rhythmicity of the slow wave characteristics was analyzed by using an EEG model of the sinusoidal waves with Markov process amplitudes which had been proposed by the authors previously. EEGs recorded from 15 subjects were modeled by the EEG model. Parameters in the EEG model were determined in accordance with the electroencephalographer's judgment as to the rhythmicity of the slow waves. The coefficient of the first order Markov process and the half-width in the model were found to be the most useful parameters for the rhythmicity of the slow waves. Automatic judgment of the rhythmicity of slow waves by using those parameters showed a good agreement with the result of the visual inspection, and the effectiveness of the analysis method using the EEG models was demonstrated.

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With the recent progress of an optical technology, the feasibility of the optical cross-sectional imaging of an animal body or an optical CT has been pointed out. The strong scattering at biological tissue is one of the most difficult problems to realize the optical CT. To suppress the scattering effect in a reconstructed image of the optical CT, a fundamental study has been conducted on the deconvolution technique using a point spread function (PSF). The image blurring due to the scattering can be considered as the convolution of the distribution of the absorption coefficient and the PSF of a scattering medium. Therefore, if we can find an appropriate PSF, we may be able to suppress the scattering effect by deconvolution using the PSF. In the conventional deconvolution technique, a single PSF defined according to the thickness of the scattering medium has been used. However, the suppression of the scattering effect has not been sufficient since the blurring effect is depth-dependent in the scattering medium. We developed a new technique to incorporate the depth-dependent PSF in the reconstruction process of the optical CT. In computer simulation, the effect of the scattering suppression was demonstrated in the reconstruction of the optical CT image.

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Functional Electrical Stimulation (FES) is very useful to restore motor functions of paralyzed extremities. It has been already reported that coordinated movements of the paralyzed upper limb of the quadriplegic patients could be restored by FES with electromyogram (EMG)-based stimulus patterns. The stimulus patterns based on EMG analysis reflect the cooperative activation of muscles. However it is necessary to measure EMG signals from many normal subjects every time when we try to restore a new movement. Hence we have studied a creating method of stimulus patterns for various movements. Stimulus patterns were created with the inverse model of the controlled object, i. e., the musculoskeletal system of the subject. Here we made Artificial Neural Network (ANN) learn the inverse model by the direct inverse modeling. Especially in this paper, the controlled object which has redundancy in an angle-stimulus voltage characteristic was considered. The direct inverse modeling method is not applicable to such redundant object. We introduced a constraint to obtain the angle-stimulus voltage characteristic which is not redundant. We controlled normal subject's wrist angles (angle of radial/ulnar flexion and palmar/dorsi flexion) with stimulus patterns created by this method. First, we measured stimulus voltage-angle characteristic of the controlled object, and obtained a forward model by making ANN learn the measured characteristic. Since the stimulus voltage-angle characteristic was many-to-one relationship, we decided one-to-one stimulus voltage-angle characteristic by using constraint. As the constraint, we minimized sum of normalized stimulus voltages to the muscles. It was expected that the muscle fatigue was suppressed by this constraint. Next, we made ANN learn the inverse model of one-to-one stimulus voltage-angle characteristic by the direct inverse modeling. Then we created stimulus patterns for four trajectories with the obtained inverse model (angle-stimulus voltage characteristic). The created stimulus patterns were applied to the muscles for wrist movements, and were confirmed to restore the desired movements. The results indicate the fundamental validity of the method.

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Image interpolation is frequently used to improve slice resolution to reach spatial resolution. Improved quality of reconstructed three-dimensional images can be attained with this technique as a result. Linear interpolation is a well-known and widely used method. The distance-image method, which is a non-linear interpolation technique, is also used to convert CT value images to distance images. This paper describes a newly developed method that makes use of end-point coordinates: CT-value images are initially converted to binary images by thresholding them and then sequences of pixels with 1-value are arranged in vertical or horizontal directions. A sequence of pixels with 1-value is defined as a line segment which has starting and end points. For each pair of adjacent line segments, another line segment was composed by spatial interpolation of the start and end points. Binary slice images are constructed from the composed line segments. Three-dimensional images were reconstructed from clinical X-ray CT images, using three different interpolation methods and their quality and processing speed were evaluated and compared.

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Since the feature of evoked potential for each stimulus may vary from stimulus to stimulus according to physical or psychological conditions of the subject, the single sweep recording method has been investigated by many researchers. In our previous work, we observed variability of the peak latency among the single sweep P300 waveforms obtained by using band-pass filter, and proposed a method to estimate the physiological variability caused by the physiological factor, by subtracting the noise variability caused by the noise of back-ground EEG from the measured variability. In this paper, we generalized the estimation method of the physiological variability for the data obtained by using the morphological filter. In order to evaluate the method, we estimated the physiological variability of the peak latency of P300 in simulation data, and obtained the accurate estimation values, which did not depend on the adopted filter (morphological filter, band-pass filter). Furthermore, the method was applied to actual ERP data of 5 healthy adults, and the satisfactory results were obtained.

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