Wakayama University · School of Social Informatics · 教授

This is a public-data preview. Personalized fit, contact angles, and saved workflows require sign-in.

• Analysis of Frontal Cerebral Blood Flow Changes in Hand Grip Force Adjustment Skill Learning.2019 · Human beings perform various motion ranging from simple motion to advanced motion. In addition, sensory information is used as a feedback information of the motion state during operations which require fine adjustment. It is necessary for performing advanced motion to acquire the corresponding skills. To learn such skills efficiently, it is necessary to construct a skill learning system. Grasping skill acquisition status is effective for the skill learning system. Currently, there is no other method than evaluating skill acquisition status by using learners' task scores. However, this method may not be enough to evaluate skill acquisition status. On the other hand, brain has the function of motion commands and sensory acceptance when moving the body. Therefore, it might be possible to sufficiently evaluate skill acquisition status by using the changes of brain activity. In the paper, we measured the changes of cerebral blood flow on learning of force adjustment skill. The obtained data was analyzed by principal component analysis (PCA) and Recurrent Neural Network (RNN). The result of PCA shows that there are some channels which have the changes of the principal component score before and after learning. In the classification by RNN, when the first principal component scores of the cerebral blood flow data before and after learning were used for input data, high classification accuracy was obtained. In addition, higher classification accuracy was obtained when using only channels which have changes in the principal component scores before and after the learning are used as input data, rather than all channels were inputted. From these results, it is shown that characteristics of the prefrontal cerebral blood flow changes according to the motor skill learning. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses)/by-nc-nd/4.0/) Peer-review under responsibility of KES International.
• Analysis of brain activity in distance recognition.2018 · Distance recognition is the skill to estimate the distance to the target object. Such a distance recognition skill is one of the most important skills in everyday life. In various situations, such as walking, driving a car, communicating with people and so on, humans perceive the distance between the targets, and do the adequate action. Generally, the precision of distance recognition is different according to difference of the ambient surroundings, the objects, and especially the individual's ability. The distance recognition is achieved by capturing the target object visually and processing its visual information in their brains. Therefore, it is important to investigate how the difference of distance recognition skills affects the brain activity. In the paper, we measure the cerebral blood flow as a brain activity by using NIRS (Near-Infrared Spectroscopy) in the distance recognition. 2018 The Authors. Published by Elsevier Ltd.
• 人工知能学大事典2017 · 人工知能学会( 担当： 分担執筆, 担当範囲: 15-27 教育エージェント)
• Measurement of Brain Activity on Force Adjustment Skill Acquisition by using EEG.2017 · Human beings perform various motion ranging from simple motion to advanced motion. In addition, sensory information is used as a feedback information of the motion state during operations which require fine adjustment. It is necessary for performing advanced motion to acquire the corresponding skills. In order to learn such skills efficiently, it is necessary to construct a skill learning system. Grasping skill acquisition status is effective for the skill learning system. Currently, there is no other method than evaluating skill acquisition status by using learners' task scores. However, this method may not be enough to evaluate skill acquisition status. On the other hand, brain has the function of motion commands and sensory acceptance when moving the body. Therefore, it might be possible to sufficiently evaluate skill acquisition status by using the changes of brain activity.In the paper, we measured the changes of EEG accompanying learning on force adjustment skill. The obtained EEG data was filtered to remove some noise using Band-pass filter, and then it was transformed into a frequency component by FFT, and the ratio of alpha wave and beta wave was calculated in the EEG data. In addition, we computed EEG coherence between the electrodes of near the frontal association cortex and the electrodes of near the primary motor cortex, between electrodes of near the frontal association cortex and electrodes of primary somatosensory cortex. As a result, the characteristics of the skill acquisition stage could be confirmed from the change of the ratio of alpha wave and beta wave, increase and decrease of the coherence values. (C) 2017 The Authors. Published by Elsevier B.V.

• シナプス可塑性を学習するニューラルネットワークの研究
• 看護の技の伝承を目的としたeラーニングシステムの構築
• 仮想実験環境における定性推論の技法を用いた認知的葛藤の制御
• 量子重ね合わせ状態に基づくユビキタスコンピューティング環境モデルの研究

• Official profile