Nagoya University · 컴퓨터과학
Keisuke Fujii 교수의 연구실은 생물학적 집단 행동과 인간 운동의 복잡한 상호작용을 비선형 역학과 데이터 기반 분석 기법을 통해 해석하는 데 초점을 맞추고 있습니다. 특히 스포츠에서의 수비 전략, 팀워크의 내재적 유연성, 그리고 개인 간의 빠른 의사결정과 반응 메커니즘을 수학적 모델링과 실험 데이터를 융합하여 연구합니다. 비선형 다이나믹스, 계층적 협동 행동, 그리고 한정된 데이터에서 잠재적인 운동 패턴을 추출하는 방식의 방정식 기반 분석 기법을 핵심으로 삼고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Groups of social organisms in nature are resilient systems that can overcome unpredicted threats by helping its members. These social organisms are assumed to behave both autonomously and cooperatively as individuals, the helper, the helped and other part of a group depending on the context such as emergencies. However, the structure and function of these resilient actions, such as how helpers help colleagues and how the helper's action is effective at multiple subsystem scales remain unclear. H
Modeling the complex collective behavior is a challenging issue in several material and life sciences. The collective motion has been usually modeled by simple interaction rules and explained by global statistics. However, it remains difficult to bridge the gap between the dynamic properties of the complex interaction and the emerging group-level functions. Here we introduce decomposition methods to directly extract and classify the latent global dynamics of nonlinear dynamical systems in an equ
With the development of measurement technology, data on the movements of actual games in various sports can be obtained and used for planning and evaluating the tactics and strategy. Defense in team sports is generally difficult to be evaluated because of the lack of statistical data. Conventional evaluation methods based on predictions of scores are considered unreliable because they predict rare events throughout the game. Besides, it is difficult to evaluate various plays leading up to a scor
We previously estimated the timing when ball game defenders detect relevant information through visual input for reacting to an attacker's running direction after a cutting manoeuvre, called cue timing. The purpose of this study was to investigate what specific information is relevant for defenders, and how defenders process this information to decide on their opponents' running direction. In this study, we hypothesised that defenders extract information regarding the position and velocity of th
Humans interact by changing their actions, perceiving other's actions and executing solutions in conflicting situations. Using oscillator models, nonlinear dynamics have been considered for describing these complex human movements as an emergence of self-organisation. However, these frameworks cannot explain the hierarchical structures of complex behaviours between conflicting inter-agent and adapting intra-agent systems, especially in sport competitions wherein mutually quick decision making an
Living organisms dynamically and flexibly operate a great number of components. As one of such redundant control mechanisms, low-dimensional coordinative structures among multiple components have been investigated. However, structures extracted from the conventional statistical dimensionality reduction methods do not reflect dynamical properties in principle. Here we regard coordinative structures in biological periodic systems with unknown and redundant dynamics as a nonlinear limit-cycle oscil
The relationship between running velocity and trunk rotation during normal running and running while dribbling was investigated in 7 male competitive basketball players and 7 male nonplayers. Participants performed a normal 20-m sprint and a 20-m sprint while dribbling a basketball. For the motion analysis, all individuals also performed normal running and running while dribbling at target of their maximal speed of sprinting and dribbling, respectively. Basketball players showed significantly sm
To clarify the defending-dribbler mechanism, the interaction between the dribbler and defender should be investigated. The purposes of this study were to identify variables that explain the outcome (i.e. 'penetrating' and 'guarding') and to understand how defenders stop dribblers by categorising defensive patterns. Ten basketball players participated as 24 dribbler-defender pairs, who played a real-time, 1-on-1 sub-phase of the basketball. The trials were categorised into penetrating trials, whe
We previously demonstrated the relationship between sidestepping performance and the preparatory state of ground reaction forces (GRFs). The present study investigated the effect of the preparatory state of GRFs on defensive performance in 1-on-1 subphase of basketball. Ten basketball players participated in 1-on-1 dribble game of basketball. The outcomes (penetrating and guarding) and the preparatory state of GRFs (non-weighted and weighted states, i.e. vertical GRFs below and above 120% of bod
Prediction of play outcomes is fundamental for sports science, engineering and practice in ballgames. Predicting who obtains a ball after a shot failure called rebound in basketball, is one of the important research subjects. To obtain the rebound, players often compete and move towards the ball drop position. Researchers have analysed important factors of a rebound using basic game statistics and video analysis. However, the most critical factors in the players’ movement to obtain a rebound are
Team sports activities are effective for improving the negative symptoms and cognitive functions in patients with schizophrenia. However, the interpersonal coordination during the sports and visual cognition of patients with schizophrenia who have team sports habits are unknown. The main objectives of this study were to test two hypotheses: first, patients with schizophrenia perform the skill requiring ball passing and receiving worse than healthy controls; and second, the patients will be impai
Understanding biological network dynamics is a fundamental issue in various scientific and engineering fields. Network theory is capable of revealing the relationship between elements and their propagation; however, for complex collective motions, the network properties often transiently and complexly change. A fundamental question addressed here pertains to the classification of collective motion network based on physically-interpretable dynamical properties. Here we apply a data-driven spectra