Misc - MIURA Hirokazu

脳波周波数を用いた数字想起状態の識別

阿児駿平,瀬戸勇記,三浦浩一,松田憲幸,瀧 寛和

次世代産業システム研究会 ( 電気学会 )    IIS-15-026   2015.03

DTNにおけるメッセージ受信のためのノード位置広告手法

中谷幸太,三浦浩一,松田憲幸,瀧 寛和

次世代産業システム研究会 ( 電気学会 )    IIS-15-033   2015.03

Analysis of brain activity in perception of pseudo-haptic using NIRS

Keijiro Sakagami, Kosuke Tanino, Yuki Seto, Shumpei Ako, Hirokazu Miura, Noriyuki Matsuda, Masato Soga, Hirokazu Taki

International Symposium on Artificial Life and Robotics     2015.01  [Refereed]

The analysis of the brain state measuring by NIRS-based BMI in answering yes-no questions

Kosuke Tanino, Hirokazu Miura, Noriyuki Matsuda, Hirokazu Taki

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 19TH ANNUAL CONFERENCE, KES-2015 ( ELSEVIER SCIENCE BV )  60   1233 - 1239   2015  [Refereed]

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In recent years, Brain-Machine Interface (BMI) has been improved with the rapid development of the cerebral function measurement technologies. BMI is used for measuring the brain activity of the subjects and inferring his/her intention. These measuring results can control the devices such as the electric wheelchair or the electric arm directly. Previous studies have such problems that BMI device is not portable, and it takes much time to attach a lot of sensor nodes on the head of the subject. Therefore, we use portable NIRS, because it is easy for the subjects to mount it and their burden is low. This paper describes the analytical method for cerebral blood flow during imagining affirmative or negative answers to the questions. It was verified whether it is possible to use the NIRS as BMI to discriminate the yes answer or no without voice and gesture. In our study, a subject keeps watching the display which shows a yes-no question, he/she imagines affirmative or negative answer to the questions. In the experiment, one test trial is in 30 seconds and it includes 10 seconds task between 10 seconds rests. Each test set consists of 10 trials. One subject has five test set. In our study, we used Wearable Optical Topography WOT-100 as measurement device of NIRS which has 10 channels (ch7-16) of prefrontal cortex. The NIRS data analysis procedure is as follows; in the first step, we used a band-pass filter to select the data of frequencies from 0.02Hz up to 0.1Hz. In the second step, measured NIRS data of each task set is divided into 10 blocks which are included 5 seconds data before the task and 10 seconds data after the task. In the third step, we calculated baseline of measured data from 5 seconds of the beginning and the end of the task blocks, and this baseline fitting is applied to the original data. In the last step, the neural network learned the important elements of the training data and classified the test data. Our method can discriminate between imagining affirmative or negative answers with 70% accuracy. At result, NIRS is useful to discriminate the yes-no answer of the questions. (C) 2015 The Authors. Published by Elsevier B.V.

DOI

思考オントロジーによる文章の論理構造の変換方法の提案

京谷 隆史, 陳 巍, 崔 亮, 松田 憲幸, 池田 満, 三浦 浩一, 瀧 寛和

教育システム情報学会 全国大会 ( 教育システム情報学会 )    2014.09

看護における考え方の指導のための添削システム

叶 秀征, 西山 大貴, 田中 孝治, 崔 亮, 池田 満, 松田 憲幸, 三浦 浩一, 瀧 寛和

教育システム情報学会 全国大会 ( 教育システム情報学会 )    2014.09

擬似力覚知覚時のNIRSとEEGによる脳活動分析

阪上慶二朗, 瀬戸勇記, 阿児駿平, 谷野広祐, 三浦浩一, 松田憲幸, 曽我真人, 瀧寛和

教育システム情報学会 全国大会 ( 教育システム情報学会 )    2014.09

NIRSを利用した文章の肯定・否定に関する脳状態の識別

谷野 広祐,瀬戸 勇記,阿児 駿平,阪上 慶二郎,三浦 浩一,松田 憲幸,曽我 真人,瀧 寛和

人工知能学会 全国大会 ( 人工知能学会 )    2014.05

エネルギーマネジメントのための属性選択を利用した制御要素の決定

藤原宏徳,瀧寛和,三浦浩一,松田 憲幸,内尾 文隆

次世代産業システム研究会 ( 電気学会 )    IIS-14-002   2014.03

車両ネットワークにおける有効距離と有効期限を考慮したデータ配布手法

三浦浩一,戸出英樹,瀧寛和

ネットワークシステム研究会 ( 電子情報通信学会 )    2014.03

DTNにおける返信メッセージ獲得のためのノード位置広告領域の検討

中谷幸太,三浦浩一,松田憲幸,瀧 寛和

次世代産業システム研究会 ( 電気学会 )    IIS-14-001   2014.03

ネットワーク型LED照明のためのカスタマイズ可能な調光制御システムの開発

鷹塀浩輔,内尾文隆,瀧 寛和,三浦浩一

次世代産業システム研究会 ( 電気学会 )    IIS-14-003   2014.03

Analysis of brain state in imaging of numeric characters by using EEG

Shumpei Ako, Yuki Seto, Hirokazu Miura, Noriyuki Matsuda, Hirokazu Taki

AROB 2014     2014.01  [Refereed]

Classification of Haptic Tasks based on Electroencephalogram Frequency Analysis

Hirokazu Miura, Junki Kimura, Noriyuki Matsuda, Masato Soga, Hirokazu Taki

Procedia Computer Science ( Elsevier BV )  35   1270 - 1277   2014  [Refereed]

DOI

Classification by EEG Frequency Distribution in Imagination of Directions

Yuki Seto, Shumpei Ako, Keijiro Sakagami, Hirokazu Miura, Noriyuki Matsuda, Masato Soga, Hirokazu Taki

Procedia Computer Science ( Elsevier BV )  35   1300 - 1306   2014  [Refereed]

DOI

Electroencephalogram Analysis of Pseudo-Haptic Application for Skill Learning Support System

Hirokazu MIURA, Keijiro SAKAGAMI, Yuki SETO, Shumpei AKO, Hirokazu TAKI, Noriyuki MATSUDA, Masato SOG

The 21st International Conference on Computers in Education     2013.11  [Refereed]

Analysis of brain state in the imaging directions by using EEG

Yuki Seto, Shumpei Ako, Hirokazu Miura, Noriyuki Matsuda, Hirokazu Taki

EMBC’13 ( IEEE )  51   R - 192-R-192   2013.07  [Refereed]

DOI

スキル学習支援のための疑似力覚生起時の脳波周波数分析

阪上慶二朗,瀬戸勇記,阿児駿平,三浦浩一,松田憲幸,瀧寛和

教育工学研究会 ( 電子情報通信学会 )  113 ( 67 ) 41-44 - 44   2013.05

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This paper describes the brain states of haptic and pseudo-haptic recognition in the skill learning supporting system. It is difficult to evaluate human cognition of haptic state only from the observation of human behavior. Therefore, to measure the biological signal of the brain, we have used electroencephalogram. We have evaluated the brain activity in the sensing tasks in order to make a comparison among the several states of the sensing of pseudo-haptic.

Development of a Dimming control system for Network type LED lighting

TAKAHEI Kousuke, UCHIO Fumitaka, MIURA Hirokazu, KANEKO Hirozumi, TAKI Hirokazu

次世代産業システム研究会 ( 電気学会 )  2013 ( 32 ) 29 - 33   2013.03

Dimming control method for LED lighting system using Android devices

KISHI Masato, UCHIO Fumitaka, MIURA Hirokazu, KANEKO Hirozumi, TAKI Hirokazu

次世代産業システム研究会 ( 電気学会 )  2013 ( 32 ) 35 - 40   2013.03