Takatomi Kubo

Nara Institute of Science and Technology | NAIST · Graduate School of Information Science

We aim to elucidate canine super-sensing, which is the ability to notice changes in human emotion. If we can elucidate canine super-sensing, we believe that it can be applied to various fields as a new sensing principle. For the purpose of elucidation, we have fabricated a device that presents stimuli to multiple canine senses. However, with the pr...

With the spread of smartphones and computer games, concerns have escalated regarding the rising prevalence of gaming disorder. Patients often display attentional biases, unconsciously turning their attention towards gaming-related stimuli. However, attempts to discover and ameliorate these attentional deficits have yielded inconsistent outcomes, po...

Drug-induced convulsions are a major challenge to drug development because of the lack of reliable biomarkers. Using machine learning, our previous research indicated the potential use of an index derived from heart rate variability (HRV) analysis in non-human primates as a biomarker for convulsions induced by GABAA receptor antagonists. The presen...

Recent time-dependent analyses of stress-related disorders have identified heterogeneity of trajectories and their modifying factors. While psychiatric patients are vulnerable to stress events, it is unclear how psychiatric conditions in the general population modulate subsequent stress responses. Using our longitudinal online survey from before th...

Background and aims Game genres, availability on smartphones, in-game purchases, and playing duration, have been thought to influence Gaming Disorder (GD). However, little research has comprehensively examined their relationships with GD. Therefore, we examined the relationship between GD, in-game purchases, gaming duration via consoles and smartph...

Dogs are a very familiar animal to us humans, but research on their cognition, behavior, and emotions is still actively being conducted. Among them, attempts at quantitative evaluation of their behavior have shown progress in recent years with the development of advanced machine learning methods. Input information used includes images, videos, phys...

Gaze behavior of human coders could allow to improve programmer-aiding tools relying on program comprehension algorithms, as gaze reveals which subsets of source code programmers focus on to understand its function. When real gaze data are unavailable, algorithmic solutions for gaze behavior estimation might be used to integrate gaze behavior in a...

Recent advanced driver assistance systems’ (ADASs) control cars to avoid accidents, but few of them consider driver’s comfort. To realize comfortable driving, an ADAS must sense the driver’s emotions, especially when they are negative. Since emotions are reflected in a person’s physiological signals, they are informative for sensing emotions. Howev...

Multi-instance object tracking is an active research problem in computer vision, where most novel methods analyze and locate targets on videos taken from static camera set-ups, just as many existing monitoring systems worldwide. These have proved efficient and effective for many established monitoring systems worldwide, such as animal behavior stud...

Physiological measurements of dogs' emotional states during human-animal interactions are essential for understanding the underlying biological relationship. Heart rate measured by electrocardiogram (ECG) can be used for the physiological measurement of emotional state. Soft disposable electrodes, which can be purchased commercially and reduce the...

Graphs are a highly expressive data structure, but it is often difficult for humans to find patterns from a complex graph. Hence, generating human-interpretable sequences from graphs have gained interest, called graph2seq learning. It is expected that the compositionality in a graph can be associated to the compositionality in the output sequence i...

The coronavirus disease 2019 (COVID-19) pandemic has profoundly affected the mental health of both infected and uninfected people. Although most psychiatric disorders have highly overlapping genetic and pathogenic backgrounds, most studies investigating the impact of the pandemic have examined only single psychiatric disorders. It is necessary to e...

Graph neural networks (GNNs) have been widely used to learn vector representation of graph-structured data and achieved better task performance than conventional methods. The foundation of GNNs is the message passing procedure, which propagates the information in a node to its neighbors. Since this procedure proceeds one step per layer, the range o...

The coronavirus disease 2019 (COVID-19) pandemic has profoundly affected the mental health of both infected and uninfected people. Although most psychiatric disorders have highly overlapping genetic and pathogenic backgrounds, most studies investigating the impact of the pandemic have examined only single psychiatric disorders. It is necessary to e...

Internet gaming disorder (IGD) and problematic internet use (PIU) are becoming increasingly detrimental to modern society, with serious consequences for daily functioning. IGD and PIU may be exacerbated by lifestyle changes imposed by the coronavirus 2019 (COVID-19) pandemic. This study investigated changes in IGD and PIU during the pandemic and ri...

The understanding of brain activity during program comprehension have advanced thanks to noninvasive neuroimaging techniques, such as functional magnetic resonance imaging (fMRI). However, individual neuroimaging studies of program comprehension often provided inconsistent results and made it difficult to identify the neural bases. To identify the...

Internet gaming disorder (IGD) and problematic internet use (PIU) are becoming increasingly detrimental in modern society, with serious consequences for daily functioning. IGD and PIU may be exacerbated by lifestyle changes imposed by the coronavirus 2019 (COVID-19) pandemic. This study investigated changes in IGD and PIU during the pandemic and ri...

Graph neural networks (GNNs) have been widely used to learn vector representation of graph-structured data and achieved better task performance than conventional methods. The foundation of GNNs is the message passing procedure, which propagates the information in a node to its neighbors. Since this procedure proceeds one step per layer, the scope o...

The article Herding mechanisms to maintain the cohesion of a harem group.

Background. Rising rates of suicide, the most dreadful consequence of mental health effects elicited by the coronavirus pandemic (COVID-19) are cause for grave concern. However, the exact association between mental health problems and suicide remains largely unknown in relation to COVID-19. Methods. To determine the impact of COVID-19 on suicide tr...

Expertise enables humans to achieve outstanding performance on domain-specific tasks, and programming is no exception. Many studies have shown that expert programmers exhibit remarkable differences from novices in behavioral performance, knowledge structure, and selective attention. However, the underlying differences in the brain of programmers ar...

Extraction of complex temporal patterns, such as human behaviors, from time series data is a challenging yet important problem. The double articulation analyzer has been previously proposed by Taniguchi et al. to discover a hierarchical structure that leads to complex temporal patterns. It segments time series into hierarchical state subsequences,...

Focal brain cooling (FBC) is a treatment for refractory epilepsy to suppress epileptic discharges from an epileptic focus. Our wearable FBC system under development consists of a recirculating coolant apparatus and a battery located extracorporeally, and a cooling device made of titanium with water channels inside which is embedded in the skull. An...

Experiments with animal models of epilepsy have consistently shown that focal cooling of epilepsy-induced brain region reversibly suppresses or terminates epileptic discharge activity. Recently, we formulated a physiologically plausible temperature dependence in a neural mass model that can reproduce the effect of focal cooling on epileptic dischar...

In animal groups, individual interactions achieve coordinated movements to maintain cohesion. In horse-harem groups, herding is a behaviour in which stallions chase mares from behind; it is considered to assist with group cohesiveness. The mechanisms of the group cohesion were studied using the methods of drone filming and video tracking during her...

Heart rate variability (HRV) is a physical and noninvasive index of the autonomic nervous system and has been used in a wide range of fields such as human medicine, veterinary and animal behavior. Measuring devices have been improved miniaturization and light-weighting and they make it possible to measure a dog's electrocardiogram (ECG) under a fre...

Expertise enables humans to achieve outstanding performance on domain-specific tasks, and programming is no exception. Many have shown that expert programmers exhibit remarkable differences from novices in behavioral performance, knowledge structure, and selective attention.However, the underlying differences in the brain are still unclear. We here...

Behavioral synchronization is shown not only between intra-species but also between inter-species. Previous studies reported that behavioral synchronization occurs between dogs and their owners by affiliative bonds and dogs' social skills for communicating with humans acquired by domestication. Horses also have such bonds and skills like dogs, howe...

In animal groups, individual interactions achieve coordinated movements to maintain cohesion. In horse harem groups, herding is a behavior in which males chase females from behind; it is considered to assist with group cohesiveness. However, the mechanisms by which the individuals move to maintain group cohesion are unknown. We applied novel non-in...

Emotional contagion is a primitive form of empathy that does not need higher psychological functions. Recent studies reported that emotional contagion exists not only between humans but also among various animal species. The dog (Canis familiaris) is a unique animal and the oldest domesticated species. Dogs have coexisted with humans for more than...

Program comprehension is a dominant process in software development and maintenance. Experts are considered to comprehend the source code efficiently by directing their gaze, or attention, to important components in it. However, reflecting importance of components is still a remaining issue in gaze behavior analysis for source code comprehension. H...

Expert programmers' eye-movements during source code reading are valuable sources that are considered to be associated with their domain expertise. We advocate a vision of new intelligent systems incorporating expertise of experts for software development tasks, such as issue localization, comment generation, and code generation. We present a conce...

This chapter introduces cyber-enhanced rescue canines that digitally strengthen the capability of search and rescue (SAR) dogs using robotics technology. A SAR dog wears a cyber-enhanced rescue canine (CRC) suit equipped with sensors (Camera, IMUs, and GNSS). The activities of the SAR dog and its surrounding view and sound are measured by the senso...

A focal brain cooling system for treatment of refractory epilepsy that is implantable and wearable may permit patients with this condition to lead normal daily lives. We have developed such a system for cooling of the epileptic focus by delivery of cold saline to a cooling device that is implanted cranially. The outflow is pumped for circulation an...

Studies on human interaction detection generally assume that interaction information is time-invariant. However, interaction may change over time, especially when time series dynamics is considered. To detect these switching interactions, we propose a segmentation-based approach. A method combining the segmentation of BP-AR-HMM and the double artic...

Most studies on human interaction detection have not considered causality. However , causal interaction detection in general is also of great interest, more so if the interaction involved changes over time. To detect these switching causal interactions , we propose a segmentation-based approach. A method combining the segmentation of BP-AR-HMM and...

We propose a segmentation method for multiple related time series data using non-parametric Bayesian methods. This method assumes that human motion follows a double articulation structure, where low-level dynamical behaviors are discovered using beta process-autoregressive hidden Markov model (BP-AR-HMM), and high-level semantic behaviors are forme...

Epilepsy is a group of neurological disorders which is caused by excessive neuronal activities in cerebrum and characterized by recurrent seizures. A quarter of patients have intractable epilepsy and do not become seizure-free with medication. We are developing an implantable and wearable focal brain cooling system, which enables the patients to le...

Search and rescue dogs are widely used in disaster situations. The efficiency of their operations can be improved if the dogs' inner states or motivation to search are estimated. We developed a real-time emotion estimation system for canines based on a measured electrocardiogram. Interval time of heart beats were measured by our canine suit equippe...

Experiments with drug-induced epilepsy in rat brains and epileptic human brain region reveal that focal cooling can suppress epileptic discharges without affecting the brain’s normal neurological function. Findings suggest a viable treatment for intractable epilepsy cases via an implantable cooling device. However, precise mechanisms by which cooli...

Although deep learning shows high performance in pattern recognition and machine learning, the reasons remain unclarified. To tackle this problem, we calculated the information theoretical variables of the representations in the hidden layers and analyzed their relationship to the performance. We found that entropy and mutual information, both of w...

A driver is regarded as a system that receives visual information and that controls the steering wheel. To identify the system, we conducted experiments to get input-output data using a driving simulator and confirmed that the focus of expansion of optical flow has sufficient information to predict steering behaviors.

Emotions of a person affect the person's performance in a task and so do emotions of a rescue dog that works after disasters. Hence, estimating emotions of a rescue dog by the handler can improve its performance and welfare. Emotions also appear in physiological signals such as heart rate variability (HRV). In fact, HRV has information of emotions...

To develop a new generation advanced driver assistance system that avoids a dangerous condition in advance, we need to predict driving behaviors. Since a nonparametric Bayesian method with a two-level structure successfully predicted the symbolized behaviors only, we applied a nonparametric Bayesian method with linear dynamical systems to predictin...

Although it is known that heart rate variability is a useful indicator of emotional states in animals, there are few reports of research in dogs. Thus, we investigated the relationship between HRV and emotional states in dogs. The electrocardiogram and behavior in two situations that elicited a positive and negative emotion, in addition to baseline...

Although deep learning shows high performance in pattern recognition and machine learning, the reasons are little clarified. To tackle this problem, we calculated the information theoretical variables of representations in hidden layers and analyzed their relationship to the performance. We found that the entropy and the mutual information decrease...

We propose a classification method based on a binary Gaussian process classifier to classify novice and experienced drivers using eye gaze that can reflect drivers' attention and skill. Gaze behavior during lane changing task were collected from both novice drivers and experienced drivers by using an eye tracking system and a driving simulator in t...

In daily life, lack of sleep is one of the main reasons for poor concentration. To support an effective napping, considered as one of good methods for recovering insufficient sleep and enhancing a user's concentration, we propose a hypnagogic time estimation using a heart rate sensor. Because a heart rate sensor has already been common, our method...

When viewing a painting, artists perceive more information from the painting on the basis of their experience and knowledge than art novices do. This difference can be reflected in eye scan paths during viewing of paintings. Distributions of scan paths of artists are different from those of novices even when the paintings contain no figurative obje...

We proposed a new scheme on automatic annotation and analysis for songs of Bengalese finches, that have variability in terms of syllable sequencing. The scheme annotates songs by using the beta process hidden Markov model, a Bayesian non-parametrics method. The annotation was confirmed to agree to the results by the manual annotation by an expert a...

Network data show the relationship among one kind of objects, such as social networks and hyperlinks on the Web. Many statistical models have been proposed for analyzing these data. For modeling cluster structures of networks, the infinite relational model (IRM) was proposed as a Bayesian nonparametric extension of the stochastic block model. In th...

Prediction of driving behavior has been regarded as one of the important issue to realize the next generation of advanced driver assistance systems. However, prediction of driving behaviors is also difficult issue, because the distribution of each driving behavior seems to be not unimodal but multimodal due to its intrinsic complexity and lack of a...

In our previous studies, an electrode grid was effective for Japanese vowel recognition from surface electromyography, and it was illustrated that a feature selection method compressing the features to one twentieth of the total features could be achieved without severe decline in recognition accuracies with one subject. In this study, we further v...

Prediction of driving behaviors is an important problem in developing a next-generation driving support system. In order to take diverse driving situations into account, it is necessary to model multiple driving operation time series data. In this study we modeled multiple driving operation time series with four modeling methods including beta proc...

Artists have a specific evaluation of abstract paintings while art novices do that with difficulty. This difference is shown in eye fixation patterns, although the cause is not clear. To explain the difference in fixation patterns, we used one of the saliency maps of paintings which predict fixations well without prior knowledge such as a meaningfu...

Prediction of driving behaviors is important problem in developing the next-generation driving support system. In order to take account of diverse driving situations, it is necessary to deal with multiple time series data considering commonalities and differences among them. In this study we utilize the beta process autoregressive hidden Markov mod...

For Japanese vowel recognition based on surface electromyography (sEMG), an electrode grid has been shown to be effective in our previous studies. In this study, we aim to leverage potential of the electrode grid further by using with a spatial shift invariant feature extraction method that can compensate deviation of the attached site of the elect...

Prediction of driving behaviors is important problem in developing the next-generation driving support system. In order to take account of diverse driving situations, it is necessary to deal with multiple time series data considering commonalities and differences among them. In this paper we utilize the beta process autoregressive hidden Markov mod...

For Japanese vowel recognition based on sEMG, an electrode grid has been shown to be effective in the previous studies. In this preliminary study, we verified efficiency of a shift invariant feature extraction that can compensate deviation of the attached site of the electrode grid in improving the recognition accuracy. 2-D dual tree complex wavele...

This paper investigates how feature selection influences the accuracy of vowel recognition based on surface electromyography (sEMG) derived with an electrode grid, which consists of densely-spaced multielectrodes. In previous studies on sEMG-based automatic speech recognition (sEMG-ASR), disc electrodes or parallel bar electrodes were used and loca...