Memorization is fundamental to human communication. However, many elderly experience memory decline with aging, which often hampers fluent communication. In order to facilitate elderlies' memory performance, positive emotions have been shown to have a beneficial effect. Particularly, elderly are more likely to retrieve positive memories compared to negative ones. However, the neural correlates of this bias has not yet been clarified within the language domain. We assessed the age-related changes concerning the role memory plays during emotional sentence processing, utilizing functional magnetic resonance imaging. A sentence judgment task and a subsequent surprise sentence recognition task were administered to 20 healthy young adults and 20 healthy elderly adults. Results of the analyses of covariance (ANCOVA) for the judgment task, using accuracy rate of the recognition task as a covariate, revealed that the elderly's accuracy rate for recognizing positive emotional sentences were correlated with their activity in the basal ganglia (BG) including the left lateral globus pallidus and the right putamen while processing positive sentences compared to neutral ones. Contrarily, such effect was not found for negative sentences.

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Time resolved spectroscopy (TRS) allows us to measure absolute values of hemoglobin (Hb) concentrations at rest. We evaluated reliability of TRS measurements of brain function. At first, we compared Hb concentrations of the frontal lobe in the morning, noon, and evening in 16 normal young adults, and found no significant difference between the times. Then, we evaluated the relation between SO2 in the frontal lobe and cognitive function measured by Mini Mental State Examination (MMSE) in 22 middle-aged people and seniors, and found significant positive correlation between them (Fig.1). These results suggest that TRS may be a useful tool for assess the cognitive function.

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Because of usability in less-restraint condition, the fNIRS measurement has been increasingly utilized for detecting human cerebral activity in many disciplines. There, however, they often suffer from motion artifacts caused by optode movement during subjects' task execution when the task includes motion. We propose a new method for removing the motion artifact caused by optode-setting instability. In such cases, the optode movement causes a signal contamination through the light reflection change at hair. In this method, the contaminants of specular reflection at hair are optically eliminated from the NIRS signal by utilizing linearly polarized light sources, detectors with orthogonally polarized analyzer, and a multidistance measurement using them. The method was validated with an optical phantom with haired surface. The optical absorbance change of a close source-detector (S-D) pair equipped with polarizers was very similar to that of distant S-D pairs even when these optodes were extraneously fluctuated. Using these signals, multidistance measurement can effectively eliminate contaminants from subject's motion as well as hemodynamics in scalp layer.

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Functional near-infrared spectroscopy (fNIRS) is a useful approach for monitoring changes in the oxygenated and the deoxygenated hemoglobin (Hb) concentration of cerebral blood flow for analyzing brain activities. However, the change includes the blood volume changes caused by the movement of the head position. The changes were superimposed on the changes in cerebral blood flow and falsely recognize it brain activity. For detecting the blood volume change, We propose an analysis method of focusing on the cross-correlation coefficient of the oxygenated and the deoxygenated Hb concentration.16-channel optical encephalography (Model OEG-16, Spectratech) was used for measurement in the forehead. A 20-year-old male-subject participated in the experiments. We applied pressure on the external jugular vein to produce blood volume change. During applying the pressure, both the oxygenated and the deoxygenated Hb concentration were increased in 11 of 16 channels. In the relevant channels, the correlation coefficient during the task period was took positive value (greater than 0.8), thus the correlation coefficient can be used for detecting the blood volume change.

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Functional connectivity in resting state has became the dominant way of understanding brain functions. However, the definition of resting states is ambiguous. A previous study have shown that low-passed dynamic random-dot patterns (DRDs) have some effects on controlling resting state, but it has not been verified enough. The purpose of this study is to define the brain activity derived from observation of DRDs. We measured NIRS signals from subjects' prefrontal cortex (PFC) and right-lateral temporal cortex (rLTC) during a block design paradigm which composed from iteration of cross hairs target and a DRD. Subjects were instructed to maintain their gaze on the cross target and to think nothing as much as possible. The DRDs were filtered by three types of Gaussian filters. As a result, the activities of ventrolateral PFC and rLTC significantly decreased when the display had been switched from the cross target to the DRD, and the effects were more intense as blurriness of DRDs increased. This suggests that observation of DRDs could be able to inhibit mind wandering and to derive attention disengagement, because these brain areas are associated with default mode network and working memory.

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Identification of human emotion from brain activities has been attracted in various research fields such as the neuromarketing. A relationship between brain activity and pleasant and unpleasant emotions has been studied using Near-infrared Spectroscopy (NIRS). In this study, we propose a method to detect the pleasant and unpleasant emotions from measurement of brain activity by NIRS using neural network. To measure brain activity under pleasant and unpleasant emotions, we used the international Affective Picture System (IAPS). The participants were 21 healthy men. Input data for the neural network were the oxy-Hb and its differential values at central part of the frontal lobe. As a result, it was shown that the method can detect emotions(‘pleasant’, ‘unpleasant’ and ‘neutral’) with the accuracy of 79% (the highest) and 65% (average). And it was found from the result that the correct rate of pleasant emotion is especially low. However, other emotions (‘unpleasant’ and ‘neutral’) can be detected with the accuracy of 97% (the highest) and 80% (average). These results show that the method using neural network can be applicable for detecting human emotions.

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Brain Computer Interface (BCI) has been studied for wide variety of applications. BCI detects human brain activities as cranial nerve information and uses the information as inputs to control machine or equipment. In some studies on BCI, Near Infrared Spectroscopy (NIRS) has been used for detecting human brain activities. NIRS gives fewer restrictions on body movement than fMRI and is less affected by electric noise than EEG. Thus, NIRS is suitable for BCI.
This paper describes the development of a portable NIRS-BCI system. We used a neural network for classification of brain activities. We used moving-averaged oxygenated hemoglobin (oxy-Hb) signals and their derivatives as the feature values. The neural network was optimized using ideal NIRS signals first. Then, we investigated their classification performance using actual data recorded in an experiment with 10 participants. Finally, a portable NIRS-BCI system was constructed with the developed classifier to show the capability of real-time operation of a robot. Experimental results showed that the portable NIRS-BCI system gives the real-time operation of the robot by the user's brain activity.

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BCI (Brain Computer Interface) is a system that controls machines and devices by extracting neural information from human brain activity and inputting it to machines. BCI system can be used to feedback the brain activity level to users so that they can control their brain activity, which is called NFB (Neurofeedback). The NFB system is expected to make better condition for ASD (Autistic spectrum disorder) and ADHD (Attention deficit hyperactivity disorder) patients. In the present study, the NIRS-based NFB system to support the developmental disorder person is developed, and the effect is verified.The NIRS-NFB system measures the brain activity by using portable NIRS. The measured brain activity can be inputted to various machines and devices (display monitor, toy car and video game). To evaluate the effectiveness of the developed system, we conducted experiments of NFB training for ASD participants. It is shown that more brain activity can be observed after the NFB training for ASD participants. Also, we confirmed that the result of POMS (Profile of Mood States) and ASD characteristic test were improved as well.Those results show that the developed system is effective in the NFB training for ASD participants.

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BACKGROUND:Near-infrared spectroscopy (NIRS) is a non-invasive and convenient tool which measures cerebral blood flow changes.In spite of its usefulness to evaluate brain functions, it is known that NIRS signals are affected by not only neural activities but also cardiovascular hemodynamics such as heartbeats.Therefore, it is important to clarify the influence of cardiovascular hemodynamics, such as cardiac output and stroke volume, on NIRS signals.METHODS:We measured NIRS signals and cardiovascular hemodynamic signals simultaneously during isometric exercise and postural change with keeping head angle in order to evaluate the influences of cardiovascular hemodynamic variables on NIRS signals independently.RESULTS and DISCUSSION:Cardiac output and the average of NIRS signals were both increased by the isometric exercise. In addition, stroke volume and the amplitude of NIRS signals, which is caused by heartbeats, were both increased by the tilt down. Therefore the average of NIRS signals would be affected by cardiac output and position of lower limbs independently.ACKNOWLEDGEMENTS:This research was partly supported by JST PRESTO and SCOPE.

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Functional connectivity is defined as spatial correlation between low-frequency cerebral hemodynamic oscillations (< 0.1 Hz) at different regions. Functional connectivity analysis is useful for brain science, so it is desired to conveniently perform the analysis based on NIRS while its signals come partly from the extra-cranial layer. The purpose of this study is to estimate functional connectivity in the frontal cortex from NIRS measurement with two kind of high density multi-distance probes. Ten healthy subjects participated in the experiments after providing written informed consent. Cerebral hemodynamic changes were measured at frontal areas in a resting state by optical topography with source-detector distance (SD) =15, 30mm or 7.5, 30mm. The effective intra-cranial hemodynamic changes were obtained by ICA (Funane's method) for SD=15, 30mm data. Functional connectivity was analyzed based on inter-channel correlation. The results showed that small SD (=7.5mm) components as well as the extra-cranial components corresponding to skin blood flow had high correlation in the whole area, suggested that the connectivity might be overestimated from 30mm components.

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In order to development of product, evaluation or decision of the likes and dislikes is important. However, objective evaluation of likes and dislikes is difficult, because the conventional method of the investigation was subjective. We got a hypothesis that objective evaluation of the likes and dislikes by an observation of the prefrontal area is possible. We had an experiment by the subjects from 11 years old to 40 years old. We show the images of nine colors to the subjects on LCD display as stimulus. We observed the activity of prefrontal area when the subjects watched images which is quantity of oxyhemoglobin by NIRS. Furthermore, we had a questionnaire about subjective order of the likes and dislikes of colors. As the result of the experiment, we found that the activity of prefrontal area increased after stimulus was shown. In this time, we also found that the activity of the prefrontal area changed if colors were different. Especially, in 80% of the subjects, when the subject dislikes the activity was higher than when the subject likes. As the result of the study, we consider that objective evaluation of the likes and dislikes is possible, using NIRS.

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It is to measure blood perfusion changes in the brain cortex that are caused by brain activation because the blood perfusion in the skin layer is included in current NIRS (Near-infrared spectroscopy) measurements. In this study, we compare performance of linear inverse method with that of depth selective back-projection filter which suppress the undesirable effects of skin circulation for a NIRS system from simulations.

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For conventional functional near-infrared spectroscopy (f-NIRS) system, the reconstruction of signals is based on simple back-projection, and it cannot distinguish the depth of the activated area. However, skin blood perfusion, which significantly varies and is affected by autonomic nerve activities, often masks the signals from a deeper target region. To improve the quality of the reconstructed images, we proposed a depth-selective space filter that suppresses the signals from the surface layer with Moore-Penrose pseudo-inversion. In this study, we performed brain-activity tests applied to forehead by using a prototype CW (continuous wave) -NIRS system which was designed for the depth-selective filter method with multi-distance channels. To validate the performance of the depth-selective filters, simultaneous measurement of Laser-Doppler flowmetry were also performed. We demonstrate the experimental results, and discuss problems in f-NIRS measurement.

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Applications of voice recognition technologies redound to carnavigation systems or mobile phones. However, cognitive-loads of voiceoperations are not discussed sufficiently. Because it is necessary totranslate a command to a verbal phrase, cognitive-loads of voiceoperations for simple tasks may become higher than those of manualoperations. In this study, we analyzed microsaccades, which are an indicator of by cognitive-loads such as attention concentration, to compare the loads between voice and manual operations objectively. Subjects performed a peripheral transition detection taskof a geometry pattern in which they responded by their voice or mouseclicks. Subjects were instructed to respond with the voice of “A” or “I” correspond to the transformation of the peripheral pattern. Theresults suggest that accuracy of detection and averaged response timeshow no significant difference between two conditions. On the otherhand, the distributions of latency of the first microsaccades showbiases immediately before or after the responses only on a voiceresponse condition. These results suggest that visual attention mightbe disengaged at the timings of response under the oral condition.

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Our previous studies have shown that motor learning is acquired faster with greater memory retention in hyper-gravity (G) environments for both goldfish and humans. This learning occurred during prism adaptation in humans, and oculomotor neural integrator (NI) adaptation in goldfish in which hyper-G was created by centrifugation. An augmented gravitation input would significantly increase vestibular input to both the goldfish and human cerebellum, in particular the vestibulocerebellum (VCB). Thus, an increase in Purkinje cell (Pkc) activity forms the basis of our working hypothesis for accelerated motor learning under hyper-G. In that event it should be possible to accelerate motor learning by using another stimulus that up-regulates Pkc activity as has been observed in the primate VCB (flocculus) in which Pkc exhibit higher dc firing rates in light than in dark. We conducted an experiment in goldfish using a white point to a black background (Darker stimulus) or black spot on a white background (Brighter stimuli). After two hours the learning curves of NI adaptation were compared and the brighter stimulus was found to induce significantly faster learning than the darker stimulus.

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The optokinetic response (OKR) of the eye is induced to follow a large field visual motion. The gain of the OKR (eye velocity / visual motion velocity) is about 0.6 at 1/8Hz in naive goldfish. If the same periodic visual stimulus is given continuously, the OKR gain increases up to 1.0. In addition to the gain increase, goldfish were found to acquire a ‘predictive’ OKR behavior that was named period tuning (PT). Thus OKR velocity decreased before the change in OKS direction as if predicting the OKS timing (Marsh & Baker, 1997). Even if the animal is exposed to complete darkness after the acquisition of PT, its eye velocity follows the similar trajectory to that during training for a while without any visual stimulation. This eye movement in the dark may share a common mechanism with optokinetic after nystagmus (OKAN), and considered to reflect characteristics of the velocity storage mechanism (VSM). To investigate the possible relationship between PT and VSM, we carried out a series of behavioral experiments in goldfish, carp, medaka, zebrafish, and human. We demonstrate that ability to acquire PT is highly dependent on OKAN. This result suggests that VSM is a key mechanism for PT.

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We have been developing the JINS MEME, an eyewear with a capability to detect eye and body movements. The horizontal and vertical EOG (electrooculogram) signals are measured and amplified with three metal dry electrodes placed near nasion and both sides of rhinion, of which positions correspond to the bridge and nose pads of eyewear, respectively. The user's mental states like drowsiness, fatigue, or interest to objects can be identified by the movements and blinking of the eyes extracted from the measured EOG. And the six-axis motion sensor (three-axis accelerometer and three-axis gyroscope) mounted in the eyewear measures the body motion. As the sensor located near the head is on the body axis, this eyewear is suitable to measure user's movement or shift of center of gravity during physical exercise with a high precision. The measured signals are used to extract various events of eye and body movement by the mounted MPU chip, or can be transmitted to the external devices via Bluetooth communication. In this presentation, the outline of the eyewear is introduced and some possible applications are shown.

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Even when we are seeing the same visual scene, visual images projecting onto the retina and those spatially sampled by retinal photoreceptors are different in each individual due to eye optics, eye movements, pupil fluctuation, and spatial arrangement of retinal photoreceptors that are unique to the individual. As such, while driving a car, some people can locate pedestrians precisely whereas others may overlook them in the same visual scene, which may cause an accident. Therefore, it is important to know retinal images of each individual to provide a personalized driving support for preventing car accidents. Here we developed a system to estimate time-varying retinal images of individuals by taking their unique eye optics, eye movements, changes in pupil diameter, and spatial distribution of photoreceptor arrays into account. We show visualized time-varying retinal images of different individuals with normal and astigmatic eye optics estimated while conducting a driving simulation. We also argue effects of miniature rapid eye movements called microsaccades on retinal images.

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Currently, many clinicians use the Yanagihara, House-Brackmann grading systems (H-B) to assess FNP. Although these assessments are performed by experts, inter- and intra-observer disagreements have been demonstrated. The quantitative and objective analysis of FNP would be preferred to monitor functional changes in patients with FNP. The purpose of this study was to introduce a three-dimensional (3-D) image generation system for the analysis of FNP and to show the correlation between the severity of FNP assessed by this method and two conventional systems. We analyzed 42 patients. Five independent facial motions were recorded with our system and the images were then analyzed using our software. The regional and gross facial symmetry were analyzed. The predicted scores were calculated and compared to the Yanagihara and H-B grading scores. The results showed that 3-D analysis could measure mouth movement in the anteroposterior direction, whereas two dimensional analysis could not. The system results showed good correlation with the Yanagihara and H-B grading scales. This system can produce consistent results that align with two conventional systems. Therefore, this method is ideally suited for use in a routine clinical setting.

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Synchrony in neuronal networks, also called a neuronal avalanche, has no characteristic scale: the distribution of the number of neuronal spikes in avalanches obeys a power law. Although neuronal synchrony is believed to replay stable spatiotemporal activity, a relationship between the size of avalanches and the spatiotemporal patterns remains unknown. Previous research reported that dissociated cortical networks under development frequently exhibited specific large sized avalanches so that the distribution of avalanches deviated from the power law. Given the previous report, if the variety of patterns correlated with the variety of avalanche sizes, a specific spatiotemporal pattern would appear dominantly during development. In this study, to test the above hypothesis, the relationship between the distribution of avalanche sizes and correlations in synchrony patterns were investigated. Cortical neurons were cultured on high-density electrode arrays and avalanches were observed through maturation. Our results showed that a characteristic size and pattern of avalanche were dominant in a specific period during development, and the sizes and patterns diversified after maturation.

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In our previous study, measurement of muscle sympathetic nerve activity (MSNA) was conducted using a micro-needle electrode and simultaneously using a noninvasive body-surface Laplacian electrode which was mounted on a high-input-impedance buffer circuit. We observed burst-like spike potentials during Valsalva maneuver in the noninvasively measured recording after the application of a modified Wavelet-based denoising. However, the specificity of the modified method was low, resulting in the merge of MSNA bursts in microneurographic recording. We hypothesized that one cause for the low specificity is mismatching between analogue and digital signal processing for rectification and integration in the current modified method. We newly introduced an exponential time window, whose time constant is consistent with that of analogue integrator, into a digital preprocessing. The introduction of the exponential time window increased correlation coefficient between digitally and analogously processed recordings after the rectification and integration from 0.92 to 0.98 on the average for 8 segments containing MSNA bursts.

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Japan is an oceanic and archipelagic country. So importance of air medical transportation (AMT)in disaster medicine of remote islands had been pointed. However most of AMT are performed by helicopters and small fixed-wing aircrafts.So there exists limitation of loading capacities, ranges,intra-aircraft medical treatments. In case of a huge disaster in remote islands such as Okinawa, many critically injured patients can not be transported rapidly in current AMT system. As a solution,collaboration of ATM and hospital ship for disaster medicine of remote islands are proposed in this study. 12vessels of Japan Maritime Self Defence Forces possess emergency hospital function with 12 operation rooms and 174 beds. Tilt-rotor aircraft AW609 has a vertical take-off and landing capability and can fly until 1300km at 510km/hr with 9 passengers. So treatments and uses of large medical equipments such as respirator,PCPS,IABP are easier than conventional helicopters. For the practical realization,problems of medical equipments used during the flight such as human-machine interfaces, power supplies, electromagnetic compatibility should be further improved.

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Many educational institutions have school-meals center inside or outside. In school-meals center, they make a lot of meals for children. But, it is a problem that the children, that have food allergies, cannot eat the school-meals. So, there are some educational institutions that makes school meals corresponding allergy ingredients. But, when the nutritionists decide school-meals and the teachers serves them, They make some mistakes, and the children that have some allergies eat school-meals including allergy ingredients. Therefore, we made a system that pay for attention to allergy and manage school-meals. We made it to reduce a burden of the nutritionists, and to supply school-meals safety. This system can manage the meals information and children information. So, it can match them information and tell the children that have food allergy conforming with each school-meals. But, it can manage the school-meals corresponding food allergies. It can propose the ingredients to use them. By supporting the alternative menu planning in consideration of nutritional value, it is possible to serving even equal meals for children with allergies.

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A major cause of fatal traffic accidents is careless inattentive driving. It has been demonstrated in many studies that sensory stimuli such as sound, smell, and vibration, are often effective, but their effects do not last long. This is mainly because our sensory information processing systems are prone to habituate quickly to a prolonged stimulus. We hypothesized that voluntary manoeuver in response to a sensory stimulus has a potential of longer lasting effects since not only the sensory system, but the sensory-motor transformation and motor systems are activated as well. In addition, if we provide rewards or punishments according to driving performance, brain areas involved in the reward system is also stimulated, which is expected to maintain alertness and attention for long enough time. In this study, during driving simulation, we evaluated deviation of the car from the center of the lane as a driving performance index together with the biological signals that are known to reflect alertness of human subjects. We found significant improvement in alertness level and driving performance in the reward/punishment conditions in comparison with control condition.

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Drowsy driving lead to a serious accident because of low consciousness. This is why driver state estimation method of accurate drowsiness level is required. In previous research, features are calculated from electrocardiogram and breathing while driving. Features are used in pattern recognition to estimate drowsiness level. But this method is unstable in estimated accuracy since value of data is not standard. Our study propose method of estimating driver's drowsiness level by using standard value of heart rate. It is considered that base heart rate during day is minimum heart rate while sleeping. We standardized heart rate during day by base heart rate. As a result, the standard deviation of data improved. We measured eight subjects for three days. After measuring electrocardiogram while sleeping, we measured electrocardiogram and breathing during drowsy driving imitation measurement by using driving simulator. By comparing estimated drowsiness level and true drowsiness level obtained from face image evaluation, we calculated rate of concordance. As a result, estimated accuracy was improved by standardized heart rate while driving using base heart rate.

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Recently, about half of traffic fatality are caused by human error. The incorrect recognition, judgment and operation while driving increases the risk of leading to traffic accident. Therefore, researchers attempt to evaluate the performance of recognition, judgment and operation by measuring reaction time while driving. Previous studies found that lowering of driver awakening level occurs delay in reaction time. However, it has not been verified how much time passed from starting to drive occurs delay of reaction time. The purpose of this study is to verify the difference in reaction time to the visual attention while long hour driving. Five subjects drove 15 lap round courses of one lap 3670m course simulating the city using a driving simulator in the experiment. We measured reaction time to LED turning on at intervals of 2-4 seconds by pushing a switch on the handle while driving. As a result, there was difference in features of reaction time to light stimulus while long hour driving.

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There are many traffic accidents due to missing safety check while driving. Therefore, we proposed “Finger Pointing and Calling (FPC)” as method of safety check while driving in previous study. FPC has effect of preventing human error and is applied many industry scenes in Japan. However, there are only a few study that verify effect on human while conducting FPC. In this study, we focus on driver behavior when they conduct FPC as safety check or without-FPC while passing intersection. We conducted experiment on a driving simulator. We analyzed driver visual movement to verify relationship with safety driving while conducting FPC. As a result, FPC increased driver's visual movement on intersection and is likely to lead to reduction of misjudge.

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Aging has been progressing quite rapidly in the world, therefore the increase in traffic accidents due to driver aging may become an international problem in the future. In order to let each individual elderly driver continue to operate vehicle safely and not to abandon driving, one needs driving support appropriate for a particular elderly driver's driving capability. We propose a method to evaluate their driving capability by tracking each individual aged person. During the investigation period spanning almost a decade, we measured the driving ability at every three-year interval for a group of elderly drivers that continue to operate vehicles. We take into consideration their natural deterioration of driving skill to build a model. Based on this model, we observe how the change in the driving skill causes our model to give various readings. Our results show that proposed model fit better with estimations when elderly drivers continue to operate their own vehicles than with when elderly drivers gave up driving. Thus, the proposed method is effective in evaluating the driving skill based on the aging of the operating capacity of elderly drivers.

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Drowsy driving is known to raise the risk of accidents. Therefore, many researcher estimate the driver's drowsy state using vehicle operation and biological signals. In our previous study, we proposed a method to predict the time of driver's drowsy state using features before driving. However, we could not reveal why prediction accuracy improved. In this study, we revealed that there are relationships between driver's state before driving and subsequent vehicle operation. After receiving informed consent from 6 subjects, they were subjected to the following experiments. To evaluate driver's state before driving, we measured subjective evaluation and biological signals. Then, we measured vehicle operation using driving simulator. We extracted driving pattern near the intersection and the traffic ‘stop sign’ from acceleration and deceleration. Then, we compared the driver's state before driving and driving pattern. As a result, when driver is different from the usual state, the probability of different driving pattern from usual driving increased. Therefore, our results showed possibility of having a relationship between driver's state before driving and subsequent vehicle operation.

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Since driver's drowsiness leads to serious accidents, it is imperative to prevent drowsy driving. Now, the event data recorders are equipped in most of taxis and buses for imaging inside and outside the vehicles. We therefore propose a detection method of driver's drowsiness by using time-series data of event data recorder for applying the active safety system.In the experiment, 4 subjects drove on a driving simulator until they fell asleep. The driver's drowsiness level was evaluated based on facial expression every 10 seconds. Analyzing drowsiness level and logged data of an event data recorder, we extracted features from forward road images. The features were highly related to increasing drowsiness and applicable to drowsiness detection in real time. Also, we included time-series variation of data obtained from the event data recorder considering the fact that the increasing drowsiness is temporally continuity.

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Drowsy driving is one of the causes of serious accident. In order to prevent such accidents, it is necessary to detect not only drowsy driving but also driver's increasing drowsiness at an early stage. In precious researches, increasing drowsiness was detected by using driver's bio-signals. However, acquiring these bio-signals on an actual vehicle is difficult because driver needs to wear the sensor and camera needs to be set up for capturing driver's face. Accordingly, this research aims at early detection of driver's drowsiness by using vehicle operation data.We examined the relation between driver's drowsiness and vehicle operation data obtained from the driving simulator. Subjects operated on the driving simulator until they drowse. Drowsiness level of each subject was evaluated based on the facial expression. From the driving simulator, we obtained vehicle operation data such as acceleration and brake pedal operation, speed and acceleration of vehicle, and lateral movement distance from the traffic lane center. We verified correlation between driver's drowsiness and vehicle operation data. As a result, we specified operation data that have relation with driver's drowsiness.

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In recent years, needs of high security environment on smartphones that can be used for electronic money is desired. Therefore, we proposed the use of the biometrics to realize higher security than the conventional password. As for the biometrics, morphological features of human body such as fingerprint and iris pattern are mainly used. We focused on the key stroke certification as a technique of identifiable biometrics authentication unconsciously. Especially, the target is flick input for smart phone. We made a flick data collection program to work on a smartphone to perform basic examination. The coordinates of point touched on the screen were taken from two subjects and evaluated it. The test results show that some features which are usable for biometric user recognition. For the next step, we will try to find additional feature parameter s and compare the parameters between subjects.

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Recently, collection and accumulation of various types of data are much easier than ever, yielding many kinds of so-called big data. In particular, as the global market of wearable devices is expected to grow rapidly and they are suitable for measuring biological signals non-invasively for a long period of time, utilizations of big biological data corrected by those devices are envisioned extensively in many fields. However, extracting information from big biological data corrected via multiple wearable devices may become burdensome as each device produces its own data in a unique format. In the current study, we developed a software environment to support handling and analyses of a large amount of data, employing the accumulated knowledge of data science. Further, we implemented a GUI application on top of this environment. The application provides an integrated platform for management of experimental data and conditions, data analyses, and visualization of analyzed data. The application was developed in Python, considering its high extensibilities by other users and availability in many platform such as Windows, Mac OSX and Linux, and thereby planned to open to the public.

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The stress is classified roughly into the distress and the eustress. The method for distress reduction is to receive counseling. However more convenient stress evaluation system is needed. We focused on onomatopoeias. Relevance of them and stress was investigated. The first purpose of this study was to develop of simple evaluation system using onomatopoeias. The second was to evaluate the system and usefulness of onomatopoeias. Ten male subjects, with their ages from 20 to 23, were participated in the experiment using the system for two weeks. After that, they answered the system evaluation test of 34 items in 5-stages. As the result, the average was 3.94. The average of the onomatopoeias evaluation of 12 items was 3.95. The numbers of distressor's answers were significantly reduced compared with the Day 1-2 and the Day 13-14. Therefore, the system evaluated as a high rate. However, the average of one evaluation item, “This system leads to distress reduction”, was 2.8. This means that the system could not reduce subjects' distress. Thus, the system needs a more clear feedback that those users are in the distress state.

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With the background of aging trend especially in industrialized countries sophisticated healthcare system installed in the house is expected to a powerful tool for keeping QOL of elderly. The term “sophisticated healthcare system” can have many definitions and also multiple perspective significance. Meanwhile, the author has recently focused on the finally showing technology of data for ordinary people including digital divide. Accumulated and analyzed data from ICT-networked sensors installed in the home must be shown to the subject in smart, not bothersome and/or easy way for any people including digital divided people. As the data providing system for ordinary people, augmented reality (AR) technology was introduced for easily implemented human friendly interface. Vison-based AR system has been attempted. As results, an example system is constructed with AR makers put on healthcare devices (blood pressure monitor and body weight meter) with networking function and another example is constructed with maker-less AR system. If one took a picture of healthcare devices with smartphone, analyzed data were automatically visualized on the display of smartphone.

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The outbreak of emerging infectious diseases frequently becomes severe are threatening people on global basis. To classify people into severe-influenza patients, mildly-influenza patients and healthy people at places of mass gathering, we developed an influenza screening system. The system conducts screening within 10 s from vital-signs, i.e., respiration rate, heart rate, and facial temperature. A neural network based discriminant function was implemented into the system to predict the infected individuals. We conducted influenza screening for 35 seasonal influenza patients at the Japan Self-defense Central Hospital. To assess the clustering performance of this system, SpO₂ was measured as a reference. The system classified 34/35 influenza patients to be mildly or severe influenza. The 10/17 severe-influenza group indicated SpO₂ less than 96%, while, only 2/17 mildly-influenza group showed SpO₂ less than 96%. This result indicates that the system has the potential to serve as a helpful tool for rapid screening of influenza in clinical settings at places of mass gathering.

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Recent measurement technologies in molecular biology allow us to obtain high-throughput human genomic information such as single nucleotide polymorphisms (SNPs). Many epidemiological studies indicate that these SNP information are useful for predicting the risk of common diseases such as stroke, diabetes or hyper-tension, and several attempts have been done for developing predictive risk models using machine learning approach. In order to improve such disease risk prediction models, we introduce in this paper a novel machine learning approach that can efficiently identify a subset of SNP combinations that are relevant to the risk of these common diseases.

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To develop large-scale detailed models of physiological and biochemical systems, establishing software framework which support such activities is crucial. Besides, as models get to be more complicated, intuitive visualization of simulation results becomes more important. In this track, we have been developing PhysioDesigner, a software platform equipping intuitive graphical user interface to support users to develop multilevel dynamical models. It can deal with not only mathematical expressions, but also time series and morphological data. Integrated time series data are used to constrain partial dynamics of the model. Recently, for improving the visualization of simulation results, we have implemented a function to automatically integrate simulation results as time series data after performing simulation, and to combine it with morphological data to replay the simulation results as animation.

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A pacemaker (PM) and an implantable cardioverter defibrillator (ICD) are devices that are inserted into the body to maintain regular heart rhythm in patients with serious heart rhythm problems. Among Japan's aging population, the number of patients requiring PM and ICD implantation has gradually and steadily increased. Therefore, a quantitative assessment of the future number of those patients is not only clinically, but also medical-economically and politically important. In this study, to develop a forecasting model for the number of patients requiring PM or ICD implantation, we analyzed past records of the number of PM and ICD implantation from 2006 to 2013 in Japan. Using a multiple regression analysis, we show the age and gender dependence of the number of PM and ICD implantation in each year, and propose a forecasting model based on age and gender composition rates of population. Moreover, as an application of our model, we estimate the future demand of PM and ICD devices in Japan.

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In the Tokyo Metropolitan Area, because it is predicted dramatically increase the number of senior citizens, it is urgent for the local government to estimate accurately the future medical demand. Therefore, we constructed an innovative simulation system with a geographic information system (GIS) to predict the future medical demand. We calculated patient numbers for every 500 square meters of the Tokyo Metropolitan Area until 2040 and estimated whether those in need could be admitted to hospitals within an hour's drive from their homes. The simulation demonstrates that patients may not be able to find hospitals within this time framework. Then, we prepared 2 scenarios. Scenario 1 was same as the existing condition, and scenario 2 reflected a previous trend of the medical treatment ratio. In scenario 1, the situation will be especially serious in the center of Tokyo and along the railway lines, where many senior citizens reside. However, in scenario 2, patients who can't find hospitals within an hour's drive has hardly appeared because of decrease of the number of patients.

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In clinical research, some data or samples can be anonymized. In linkable anonymizing, linkable information, which links information for personal identification to anonymized data or samples are generated. In view of privacy protection, linkable information should be controlled properly. We developed a method to refer to encrypted likable information without decryption by using searchable encryption for secure data management. Although this method will strongly enhance the protection, it takes a long computing time to retrieval. We apply additional approach ‘index’ to our system, which employs data structure for efficient retrieval to reduce search time of encrypted linkable information.

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Ministry of Health, Labor and Welfare was established health welfare PKI certificate policy. Medical Information system development center(MEDIS) were constructed health welfare Public Key Infrastructure electronic certificate authority in accordance with the certificate policy the Ministry of Health, Labor and Welfare was established. MEDIS have created a health care electronic signature service practice statement that defines such detailed operation method for production further. MEDIS has also established a well as regional acceptance examination stations paperwork procedure that becomes its subordinate provisions class. Electronic certificate of this MEDIS can be issued doctor, dentist, pharmacist, etc. 24 kinds of health care workers national qualification holders. MEDIS publishes the electronic certificate without mention of the national qualification besides. This certificate is to electronic scans the medical records of the paper in the hospital, has been utilized, such as when it save as original. In MEDIS, it has been conducted a questionnaire survey about the popularity of HPKI as targets such as vendor maker of health care workers and medical information systems, it was found that still name recognition is low.

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In this study, link control technique using multiple photo detectors is introduced to avoid disconnection of the optical wireless link for optical telemetry. At the mobile terminal, link control is executed by direction detection of a base station evaluating received signal intensities of photo detectors which have orthogonal directions of sensitivity (fig.1 (a)) and radiating the uplink signal to the base station. We evaluated the effectiveness of the link control technique using the experimental system (fig.1 (b)). As the results, the effectiveness of proposed technique were confirmed within the transmitting area covered by 7 meter radius from the base station.

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To realize practical optical communication through human body, an experimental study was conducted using the near-infrared light through a human hand. A wrist-watch type light transmitter was made and the possibility of the optical signal transmission from the wrist to the fingertip was confirmed. A practical light receiver was installed in a door-knob. Fig.1 shows a wearable light transmitter and a door-knob type receiver. The feasibility of the optical data transmission through the adult hand was verified. The optical radiation from the hand was found to be confined in close proximity (within 100 mm range) of the hand. This controllability of radiation guarantees high security in practice.

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In this study, the authors propose a method to estimate the position on an air bed by internal pressure change. The pressure of a bed varies by the position because the contact area between body and bed changes. The experimental system uses a commercially available air bed and a gauge pressure sensor. The figure shows measured pressure change according to the position. From this result, prone or supine position and lateral position are easily discriminated from the pressure difference. Furthermore, sitting position and fall from a bed were clearly detected. But prone or supine position and left or right lateral position can't be discriminated in principle.

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We examined the detection method for wake-up behavior using visible ray camera to predict patient's ambulation behavior in advance. In our past studies, we proposed a method that configured mask patterns by using the edge instead of CHLAC feature. The study furthermore showed that the wake-up behavior was detected with high accuracy compared to using CHLAC feature by combining with the process where the abrupt slope changes were dealt as noise in the mask pattern configuration. However our conventional approach did not deal the cases where the edges with different gradient directions on the same object presented the same movement. For example, when a boll is moving, each outer edge has different gradient direction but the moving direction is the same. Since each of the movements of the outer edge is the information that expresses the movement of the ball. itself. In this paper, we propose the method where, by convolving the feature vectors of the same movement without performing the conventional noise reduction process, they are dealt as the same feature. The examination result has confirmed the detection rate of our method has improved by 25[%] compared to the conventional method.

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The sleep is essential for maintaining the human health. Sometimes, sleep problems are caused of the drop of the work, the decrease of work efficiency, and drowsy driving with the diversification of the lifestyle. Therefore, it is necessary to focus on a sleep monitoring. In the case of monitoring sleep, PSG measurement is common as a measurement method of the sleep depth. However, this method has to attach many electrodes to subjects. So subjects feel constrained and it would be cause of heavy stress. Therefore, it is necessary to develop a new method that can measure the sleep state under the unconstraint and noncontact condition. In this study, we performed the sleep measurement experiments by the PSG measurement and electric wave sensor. The electric wave sensor could measure the body movement, the respiratory frequency and the respiratory amplitude. Finally we inspected whether we could estimate the sleep depths. The average of the body movement became small during the awakening degree decreases. The average of the respiratory frequency did not have a big difference in each sleep stage. The average of the respiratory amplitude became small as well as body movement.

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In this study was investigated how to enlarge the contact area of the body surface in order to improve the body pressure dispersion performance in the mattress. We have developed a mattress, by controlling the shape and the fixed and the pressure of the air cell can be deformed to the same pair surface shape, and air cells is along the body surface shape, and can be supported in a distributed weight. As a result was shown in figure. For mattress was placed on the surface of the air cells, a decrease in body pressure was observed by controlling the air cells. It is not to centrally the body pressure in the bone protrusion in dorsal position.

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The purpose of this study was to clarify the changes in the rectal pressure and the circulatory system between sitting and supine positions in defecation with taking pressure.
Twelve healthy volunteers (age 22 ± 2 years) consented to participate in this study. They performed ①the maximal pressure into the abdomen, ②the rectal pressure at 20 mmHg in supine and sitting positions for each 15 sec in the end of inspiration. The intrarectal pressure (RP), blood pressure (BP), heart rate (HR) and muscle activity were recorded continuously with Intercross330.
In the maximal pressure into the abdomen, RP was higher in sitting than supine (sitting vs supine: 33.0±10.3 vs 23.6±7.7 mmHg, p=0.010).The change in BP was greater in sitting than supine (sitting vs supine: 54.2±24.5 vs 28.2±10.1 mmHg, p=0.003). In the rectal pressure at 20 mmHg, there were no significant changes in BP.
In conclusion, when straining pressure, RP becomes higher in sitting position than supine. It's easier to defecate in a sitting position, because the strain is transmitted in the rectum effectively. There were not significant between the two postures in the change of BP on the same RP in defecation.

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A combination of pad-type and pants-type disposable diapers are used in nursing homes for the elderly in Japan. In this study, a torso was fitted with a pad-type diaper and a pants-type diaper. Electrodes were attached to the outside of the pants-type diaper to evaluate the urine absorption volume of the pad-type diaper. The capacitance of the electrodes increased linearly with the increase in the water absorption volume of the pad-type diaper. A subject wore the diapers and the electrodes and discharged his urine into the pad-type diaper. The capacitance of the electrodes increased, and the urine absorption volume was estimated by the increase in the capacitance of the electrodes.

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