Object recognition requires discrimination across different objects in spite of the view change of the same object. In our previous experiment, single neurons of inferotemporal cortex responding to the training object sets that the monkeys had experienced in association between views of the objects across up to 90 deg in viewing angle responded with a viewing angle tuning curve width of about 60 deg. To reveal the neuronal mechanism underlying the association training, we analyzed the response patterns of cell population to the object images experienced in the object discrimination across up to 90 deg. We found that the similarities for response patterns of views of the same objects were significantly larger than that across different objects for viewing angle difference of 30 deg, 60 deg, and 90 deg. The results suggest that the object discrimination across large viewing angle could be explained by the neuronal activity of cell population in inferotemporal cortex.

The electrical activity of the gastrointestine is measured using an electrogastrograph and presented as an electrogastrogram (EGG). Electrogastrography is a noninvasive procedure to evaluate gastrointestinal motility and autonomic nervous system activity. However, EGG do not have been applied to clinical fields as electrocardiogram and electromyogram because EGGs are often contaminated by electro activity in the myocardia and muscles of diaphragm with respiration; furthermore, we do not understand the relationship between EGG and the gastrointestinal motility. Analytical methods of the EGG do not have been established yet. In this paper, the author compared an EGG measured in the abovementioned experiment with numerical solutions to the mathematical model describing the EGG. It is known that the van der pol equation (VPE) is appropriate for obtaining a mathematical model of the EGG because the waveform of the electric potential in the Cajal cells is similar to the graphs of numerical solutions to the VPE. In our previous study, the mathematical model, a system of stochastic differential equations (SDEs), was improved by adding the VPE to a periodic function and random white noises that were analogous to the intestinal motility and other biosignals, respectively. The numerical solutions were quantitatively evaluated by comparing with the distribution of the EGG, its translation error E_trans estimated by the Wayland algorithm, and E_trans' estimated by the Double-Wayland algorithm which was sensitive to stochastic variations.

The layered structure in the cerebral cortex has an important role in expressing brain function and is formed by cell migration during embryogenesis. However, it is not clear how neurons migrate and form layers orderly because an appropriate culture method is yet to be developed for evaluating cell migration. Our purpose is to develop an experimental system to control directions of human-neuronal migration in two-dimensional culture in order to understand the mechanism of neuronal migration during corticogenesis. Here, we made a stripe pattern of laminin on culture dishes, and cultured human induced pluripotent stem cell (iPSC)-derived neural cells on the pattern. iPSC-derived neural stem cells and neurons extended their fibers along the pattern. Then, migration of neural cells on the pattern was traced with time-lapse imaging. As a result, the migration length along the pattern was significantly longer than that orthogonal to, suggesting that the laminin pattern guides effectively neural-cell migration. Our method using the laminin pattern should be appropriate for controlling and observing human-neural-cell migration, and moreover, applicable to the study of revealing the mechanism of the migration.

Here we report the development of a personal identification number (PIN) application using a P300-based brain-computer interface (BCI). We focused on visual stimulation design for increasing the evoked potential in the brain. Single-channel electroencephalography and a computationally inexpensive algorithm were used for P300 detection. Experimental results showed that our proposed stimulus induced higher P300 amplitude than did a conventional stimulus. For a performance evaluation, we compared two versions of the proposed application, which were based on our ‘original P300 BCI’ and ‘adaptive P300 BCI’. In the adaptive P300 BCI, we introduced a novel algorithm for P300 detection to improve the information transfer rate while maintaining acceptable accuracy. Experiments with 10 healthy participants revealed that the original P300 BCI achieved mean accuracy of 83.50% at 11.40 bits/min and the adaptive version achieved mean accuracy of 86.00% at 18.63 bits/min.

In this research, a hands-free remote operation system for a mobile robot using electrooculogram (EOG) and electromyogram (EMG) is developed. The EOG and EMG signals are acquired from one set of electrodes on temples and these are separated by bandpass filter. Four control commands of mobile robot motion generated by processed EOG and EMG signals are transmitted to the mobile robot via wireless communication. Experimental results show the effectiveness of the proposed remote operation system.

A Brain-Computer Interface (BCI) enables users who cannot move their own body freely to manipulate machines. Recently, a system which is a combination of BCI and Augmented Reality (AR) is proposed. This system can link real machines to augmented markers and realize an intuitive interface. However, conventional AR-BCI system uses only visual stimuli, so a user cannot operate machines behind him/her. To deal with this problem, we propose a multisensory AR-BCI using three dimensional stereophonic sound, which provides choices behind users by generating sounds including position information. First, we investigate the amplitude and latency of event-related potential (ERP) induced by three dimensional stereophonic sound. The result shows the latency of ERP is longer (650 ms) than conventional BCI. This result suggests that the feature should be extracted with a longer time window. Second, we compare the accuracy of separate classification with combined one under the mixed visual and auditory stimuli. The result shows separate classification is better than combined one (p<0.05). Therefore, our research proposes separate classification method which comes from the basic features of ERPs under multisensory AR-BCI system and shows the appropriateness of proposed method.

To examine changes in somatosensory cortical activity associated with the processing of emotional images, we measured steady-state somatosensory evoked fields (SS-SEFs) of magnetoencephalograms (MEGs) under tactile stimulation. We used the International Affective Picture System (IAPS) which is increasingly used in brain imaging studies to examine emotional processes. Their images also allow valence to be systematically investigated. Those images, along with synchronous tactile stimuli, were randomly presented for 2.0 s using a video projector and a screen set at 120 cm in front of the subject. The tactile stimuli were applied to the tip of the right index finger. A stimulus epoch consisted of a 2.0 s period of vibration at 10-Hz or 20-Hz and a silent period of 1.0 s. At least 50 epochs were recorded for off-line averaging of the MEG signals for each condition of negative, positive, or neutral images, according to the prior categorization by each subject. The amplitude of the SS-SEF was larger for the negative impression images than for the neutral impression images (p < 0.05), suggesting that the amplitude of the SS-SEF that originated from the somatosensory cortex was modulated by the visual emotional stimuli.

Assessment of myocardial perfusion in 2D X-ray angiography image during coronary interventional treatment is important for better patient outcome. It is necessary for 2D image signal intensity to lineally relate with amount of contrast agent in body for quantitative perfusion analysis. However, it is not linear because of scatter and beam hardening. The aim of this study is to propose simple and practical calibration method for linear relationship. The image signal intensity of the catheter is used to estimate scatter ratio and patient body thickness, and to generate correction function. This correction function is applied to all 2D image pixels to generate corrected image. For verification, 370 mg/ml iodine contrast agent in a 2-mm-diameter silicone tube was used, and correction function was generated. The generated correction function was used to correct image signal intensity of 15 different amount of contrast agent. The corrected image signal intensity were compared with the actual. The mean error between the actual and estimated value was 4.8%. The linear regression line slope was 0.97 and correlation coefficient was R=0.998. The proposed method was confirmed to achieve a good linear relationship between 2D image signal intensity and amount of contrast agent in body.

In this study, we propose a hybrid brain/blink computer interface based on a single-channel electroencephalography (EEG) amplifier. Eyelid closing and hard blink were selected as two possible inputs for control of the interface. A 2-min calibration was required before starting to use the interface. An algorithm for feature extraction and classification was developed for EEG signals from eyelid closing, hard blink, and resting. To evaluate the performance of the interface, we incorporated it into a personal identification number (PIN) application, in both visual and auditory modes. Experiments with 5 healthy participants revealed that the PIN application based on the interface achieved a mean accuracy of 97.40%. In conclusion, we expect that our investigation will contribute to hybrid brain-computer interface research and technologies in the near future.

Downhill turning of a wheelchair on a cross slope is one of the risk factors in driving. To prevent this unintended change of a track by the gravity, downhill turning prevention control (DTPC) has been developed and widely used for power wheelchairs. However the effectiveness of DTPC has not been quantitatively evaluated. In this study, we investigated DTPC-induced changes in joystick operation and wheelchair behavior by test drives on a cross slope. The results of data logging during the test drives, where ten users of a power wheelchair participated, successfully demonstrated the effects of DTPC. The offset operation of joystick to turn uphill on the cross slope was decreased by DTPC, providing an evidence that the burden of manual control was reduced. The evaluation measure related to wheelchair veering was also significantly decreased. These results quantitatively indicate that DTPC improves driving stability of a power wheelchair and thus its safety on a cross slope.

Dual-task paradigm is a behavioral procedure in which subjects are required to perform two independent tasks in parallel, each of which involves a distinct stimulus-response association that leads to a unique goal. Although dual tasks are widely used in human studies, they are seldom used in animals. One such rare case was a rat simultaneous temporal processing (STP) task, in which rats were asked to time two different intervals simultaneously⁽¹⁾. However, there are a few limitations in this paradigm, such that, for example, each of the two component tasks was not clearly associated with a unique stimulus-response association. In this report, in order to better characterize temporal dual-task performance in rats, we developed a modified version of the STP task that was comprised of two clearly-divided component tasks, and equipped our experimental system with a novel video-based motion tracking system. We show that even under this more rigidly controlled dual-task setting, rats are able to time two different intervals virtually without interference, and that our tracking system can simultaneously detect head-direction and body-location of a rat with high accuracy. These results suggest that the present experimental paradigm should be useful for investigating cognitive processes that underlie dual-task performance at both the behavioral and neuronal levels.

Cultured rat hippocampal network on a multi electrodes array (MEA) dish is useful for analyzing the relationships between electrical activity and culture condition during developing the networks. Seeded neurons autonomously form a complex network on a MEA dish and autonomous electrical activity is often observed without any inputs from outer world. Autonomous activity is considered to reflect internal states of the neuronal network. We elucidated that there are a particular relationship between autonomous activity and glucose concentration of culture medium at 7.5 mM, 17.5 mM and 30 mM during developing neuronal network. In the case of 17.5 mM glucose concentration, We confirmed that the frequency of autonomous electrical spikes increased accompany with culture days. In the case of 30 mM glucose concentration, trend of autonomous activity was similar to the case of 17.5 mM. Thus, in the case of 30 mM glucose concentration, glucose neurotoxicity was not obviously observed. Also in the case of 7.5 mM glucose concentration, frequency of autonomous electrical spikes similarly increased during culture days, however, the frequency was significantly low comparing width the case of 17.5 mM glucose concentration. In addition, the frequency of electrical spikes in the condition of 7.5 mM glucose concentration and the initial density of 7800 cells / mm² was similar to the frequency of the spikes in neuronal networks cultured at the initial density of 2600 cells / mm² or 3900 cells / mm² in 17.5 mM glucose concentration. These results show that neurons adjust the culture size and electrical activity to the glucose concentration of culture medium during developing a neuronal network.

This paper was to consider methods to sensitively detect the effects of environmental pollution. A variety of environmental pollution exists in Japan and abroad, and biomonitoring with organisms is the main way levels of pollution in environmental specimens are determined. This paper considered changes in pH due to industrial effluent, sodium sulfite, and NaCl as factors for pollution. Physarum polycephalum is a protist that is sensitive to environmental pollution. This paper examined the effects of pollution on ATP levels in P. polycephalum and this paper explored the potential for these effects to serve as an index of environmental pollution. Results indicated that ATP levels were lowered by (1) a rise in the pH of a mixture of sulfuric acid and nitric acid, (2) increased levels of sodium sulfite, and (3) increased levels of sodium chloride. In addition, ATP levels and factors for environmental pollution were also examined. Results revealed the tolerance limits of P. polycephalum to pollutants. Thus, results revealed that ATP levels decrease as a result of environmental pollution. Results also suggested that ATP levels cannot be used as a pollution index since ATP levels cannot sensitively detect the effects of environmental pollution.

Nerve conduction test is a noninvasive method to find some possible malfunction of a peripheral nerve to conduct action potentials between stimulation and observation points by observing the compound action potential after stimulation. To obtain the basic method to estimate the effect of composition and shape of a limb to the test results, compound action potential produced on the surface of a cylindrical limb was simulated using boundary element method. The produced potential wave had a typical shape of a compound action potential and conducted at rational velocity.

Input systems using eye blinks have been proposed. A main purpose of these systems is communication aid for the severely disabled. For employing eye blinks as a command input, these input systems need to detect voluntary (conscious) blinks. We developed a measurement method for variation in pixels of open-eye area from an image sequence. This measurement method enables us to extract blinking wave patterns. We previously proposed an automatic classification method between one type of voluntary blinks and involuntary (unconscious) blinks. If the types of classifiable voluntary blinks increase, we can assign an individual command to each type. Applying this blink type classification to a human-computer interface will improve the efficiency when inputting commands. In this paper, we introduce a new type of voluntary blinks to increase classifiable blink type. In addition, our classification method is extended for automatic classification between two types of voluntary blinks and involuntary blinks. This new classification method is realized by two blink type determinations based on wave pattern parameters that we employ. We clarify proper parameter combinations for the new classification method. Using these proper parameter combinations, we achieved approximately 95% classification rates for 10 subjects.

Energy management systems (EMSs) have been widely developed for efficient energy usage. Optimization of operation of energy consuming plants is one of key technologies in EMS. In this paper, we propose a very fast optimization method for optimal load distribution problems by which we can implement optimizing functions on microcomputers without high speed CPU or rich RAM. The proposing method consists of two phases, offline formula manipulation phase and online fast calculation phase. We show that the proposing method can give a strict optimal solution without any violation of constraints within 96 times shorter time than a traditional gradient method. The proposing method can contribute low cost and ubiquitous optimization for EMS.

It is becoming important for working robots to be able to identify and pick objects in various tasks. As in the recent Amazon Picking Challenge, using a marker for the picking task is a more practicable approach. However, a common marker code for working robots does not exist so far. Conventional marker codes as represented by QR code or ARToolKit marker cannot be reliably detected from various viewpoints. Thus in this paper, we propose a new encoded marker which is flexibile to the marker's positions and blur. The proposed marker can be detected by an approach based on the scale space theory independent from such conditions. In addition, the representation of data by M-sequence makes the encoded marker robust to blur. Experimental results showed the effectiveness of the proposed marker compared to the ARToolKit marker. Since the marker is more robust against ground clutter noise, various positions of markers and blur, it is more practicable.

Audio-visual combinations in multimedia contents give us more exciting experiences than only audio or visual information. To support audio-visual video creators, affective impressions of audio-visual contents have been explored to date. However, little research has analyzed in terms of structures or features of audio-visual contents. Revealing relationships between audio-visual impressions and their structures or features can be helpful for video creators. The current study aims to analyze effects of music on image impression in terms of musical features. Specifically, we asked participants to rate impressions for image stimuli at two conditions in which image-only stimuli or music-image combination stimuli were presented. Three factors representing image impressions were extracted by factor analysis, and differences of factor scores between two conditions were calculated to describe impression changes by music. We confirmed relationships between impression changes and musical features (e.g. volume, pitch, and timbre) by ridge regression analysis. As a result, regression analysis accounted for high variances in amount of impression changes and revealed that some musical features influenced on image impressions. This study provides a feasibility of estimating image impressions by musical features.

In recent years, analytical method in which the length of time-window for time-localization can be established optionally was shown by the authors. If you decide the time-window width which is in inverse proportion to the frequency, The function becomes the same as the elastic function of the mother wavelet of wavelet transform, and the same effective analysis as wavelet transform is carried out. Since the processing of this analysis is independent almost completely, approximately complete parallel processing is possible. Analysis in real time is carried out by introducing parallel processing. In this analytical method, we use a sine wave and cosine wave of plural periods, and so we call these waves a cutting out wave and call the plural periods a number of periods. We use inner product of the cutting out wave and the signal. The number of periods determines the size of the width of time-window. If width of time-window is enlarged, frequency resolution will improve, but time resolution falls. It is impossible to improve the frequency resolution and the time resolution simultaneously. This is the uncertainty principle. In this analyzing method, it's analyzed by many signal detection unit. At first a signal is performed by all signal detection units, and I call this first stage analysis. Next we analyze the wave that appears in each signal detection unit in first stage by using the same signal detection unit again. This is second-stage analysis . This is repeated and plural stage analyses are conducted. This is multi-stage analysis. It is shown that the frequency resolution can be improved in spite of uncertainty principle by this multistage analysis.

Ever since the international standard JPEG 2000 based on the lifting wavelet transform was adopted as a core technology of the digital cinema applications, its implementation issues have been discussed from various respects such as memory band width, low latency, high throughput, parallel processing and so on. Unlike the separable two-dimensional (2D) structure of the conventional lifting wavelet transform, the non-separable 2D structure can minimize the total number of lifting steps. It reduces latency of the transform on a parallel signal processing platform at the cost of introducing 2D memory accessing. However, when the word length of coefficient values inside the transform are shortened, the non-separable 2D structure has a problem that its output signal is heavily damaged by the truncation of the coefficient values. Especially, a few coefficients are extremely sensitive to the truncation in this structure. Therefore a careful treatment is required to these sensitive coefficients. In this paper, after investigating the sensitivity of each of the coefficients, a tolerable truncation error is optimally allocated to each coefficient based on the measured sensitivity. As a result, a cost function of the total word length of the wavelet transform is reduced maintaining the total amount of the noise due to truncating the coefficient values. The method is applied to expressing the coefficient values in the sum-of-power-of-two (SPT) format for a low computational load implementation.

The analysis of human motion is a challenging research domain that attracts the attention of researchers from several disciplines, including sociopsychology, neurobiology, and computer science. A successful recognition of the person's walk could be used for personal identification, and also, would be important for understanding the human's emotions, personality, and neurological disorders. However, recognizing the human gaits is a challenging task because of the complexity of the eventual analytical model that defines the numerical relationship between the relevant features of the gait. In our previous work we proposed an approach of applying genetic programming to automatically design such a model in a way much similar to the evolution in nature. In this paper, we continue the focus on human gait recognition, and present an analysis of the trade-off between the evolution of genetic programs (GPs) and their performance. We consider different training cases, provided that the computational resources and other parameters are kept constant. Furthermore, in our previous work, there was an important unanswered question regarding the effect of the increased number of fitness cases and the use of experts in collaborative filtering on the evolution of GPs and gait recognition. This study is an attempt to explore the same unexplained question.

A method is proposed for quantifying the performance of air conditioning systems by using data recorded by a typical energy management system (EMS). An EMS measures the cumulative energy consumption, instantaneous flow amount, temperature of the heat medium, and environmental air conditions, and it typically keeps a record every 1 hour or so. This makes it difficult to quantify system efficiency from these values. The proposed method derives an efficiency value from the distribution shape pattern of the data calculated from these inconsistent data. Applying the proposed method to the data of a site, it produced more stabile results than did the pre-existing method usually applied to business performance analysis. Using 1-min. sampling data, we show that the proposed method extracted the characteristics related to static operation.

For the subject to actualize a noninvasive and continuous monitoring technique of blood viscosity, we had demonstrated that the peak frequency of the ultrasonic reflection spectrum was an effective index by using red blood cell-mimicking particles. The reasons for using the particles were (i) the control difficulty of the aggregation degree, which had a strong correlation with the blood viscosity, and (ii) the weak reflection coefficient of the red blood cells in the plasma. In this paper, a possibility of the quantitative control of the red blood cell aggregation and an agreement between the aggregation degree and the peak frequency obtained using the actual porcine blood are described.