九州大学 研究者情報
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片山 喜規(かたやま よしのり) データ更新日:2019.06.14

助教 /  システム情報科学研究院 情報学部門 知能科学


主な研究テーマ
ブレインコンピュータインタフェースを志向する脳波信号処理
キーワード:ブレインコンピュータインタフェース BCI 脳波信号処理 EEG アーチファクト TMS 経頭蓋磁気刺激
2008.05.
オンライン文字認識におけるキューブサーチHMMの学習法とストロークHMMモデルの検討
キーワード:オンライン文字認識 筆順フリー キューブサーチ HMM フック
2006.04.
研究業績
主要原著論文
1. Kazuki Onikura, Yoshinori Katayama, Keiji Iramina, Evaluation of a Method of Removing Head Movement Artifact from EEG by Independent Component Analysis and Filtering, Advanced Biomedical Engineering, DOI:10.14326 / abe.4.67, 4, 67-72, 2015.03, Artifacts that contaminate electroencephalography (EEG) signals make it difcult to analyze EEG. The aim of this study was to removal artifacts on EEG, especially those caused by motion, to measure EEG in unconstrained situations. In a previous study, head movements were detected by an accelerometer, and motion artifact components were separated from the recorded EEG by independent component analysis (ICA). This method is effective for reducing the effect of artifacts, but has a risk that EEG components are also removed.
In this paper, we introduce an improved artifact removal method based on ICA and filtering. EEG were decomposed by ICA, and a Pearson’s correlation coefficient was calculated between each independent component and each hybrid accelerometer value to distinguish artifact components. Artifact components were then high-pass filtered. In this study, subjects were instructed to move their heads randomly, while keeping their eyes closed. The previous method was adapted using 1, 2, 3, 5 and 10 s to find the most suitable epoch to minimize the mean absolute amplitude of the cleaned EEG. Then, using this epoch, the proposed method was compared with the previous method by frequency analysis.
Low frequency power (0.1–3 Hz) was normalized to unity because most power caused by motion artifacts exists in the low power band. If the normalized theta (4–8Hz), alpha (8–13Hz) and beta (13–40Hz) powers of cleaned EEG are higher than that of raw EEG, this indicates that the effect of motion artifacts is small and EEG components are retained.
The results obtained from theta and alpha power comparison showed that the proposed method performed better than the previous method. This result suggests that the proposed artifact removal method is more effective to reduce the effect of artifacts while retaining the EEG components..
2. 片山 喜規, 経頭蓋磁気刺激等の生体磁気にまつわる近況
, 電気学会, 10.1541/ieejfms.134.6, 134, 1, 6-9, 2014.01, Recently the biomagnetism and its medical applications become popular than ever, by understanding the usefulness of it (such as MRI) widely spreading among people. The noncontact and noninvasive features of the magnetic applications reduce the risk of subjects. This paper introduces recent trends around the biomagnetism and its medical applications slightly focusing on the recent topics about the transcranial magnetic stimulation (TMS)..
3. Fumiyoshi Matsusaki, Yoshinori Katayama, Keiji Iramina, Influence of TMS Coil Orientation in the Simulation of Neuronal Excitation by TMS Using an Axon Model and Cerebral Cortex Model, Advanced Biomedical Engineering, DN/JST.JSTAGE/abe/1.55, 1, 1, 55-59, 2013.06, Transcranial magnetic stimulation (TMS) allows non-invasive and painless stimulation of local
cerebral nerves using eddy current generated by electromagnetic induction with a TMS coil. Although TMS is
used in various fields, which area of the brain is stimulated is not known because of the complicated structure of
the organ. In this study, we simulated neuronal excitement by TMS using the finite element method. First, we
designed a brain sulcus model consisting of cerebrospinal fluid, gray matter and white matter, using 0.5 mm cube
elements. To improve calculation accuracy, cube element size was set to 0.5/3 mm only in regions near the
boundary surface. Second, we applied TMS stimulation to the model in different conditions. We used coil radii of
10, 20, 30 and 40 mm, and coil orientation at 0°, 30°, 45°, 60° and 90°, which is defined as the angle between the
orientation of the electric field and the axon. Finally, we calculated the membrane potential and compared the
results obtained under different conditions. We found that membrane potential changed rapidly at the white
matter and gray matter interface when the coil radius was over 20 mm and coil orientation was within 60°
between the orientation of the electric field and the axon. These results provide useful information on appropriate
TMS parameters for effective stimulation of target area in the brain..
4. Y. Katayama K. Iramina, Fitting and Eliminating to the TMS Induced Artifact on the Measured EEG
by the Equivalent Circuit Simulation Improved Performance
, 5th Kuala Lumpur International Conference on Biomedical Engineering 2011: Biomed 2011, 20-23 June 2011, Kuala Lumpur, Malaysia (Ifmbe Proceedings), 10.1007/ 978-3-642-21729-6, 35, 519-522, 2011.06, Transcranial magnetic stimulation (TMS) is the non-invasive stimulus method to the brain by inducing the eddy current within the brain from the TMS coil placed outside the scalp. The induced eddy current stimulates the nerve circuit causes to suppress the brain activity partially in time and space, and it is applied to detect the brain functions etc. When TMS is applied to the brain while measuring the electroencephalography (EEG), the induced artifact caused by TMS covers on the EEG, it is called the TMS artifact. The amplitude of the TMS artifact is generally too large to omit diagnosing the EEG. Therefore some methods have been proposed to negate the TMS artifact from the EEG including the TMS artifact using the EEG only. We proposed a new method for describing the shape of the induced artifact in the EEG applied TMS using two equivalent circuit models, the TMS equipment model and the equivalent circuit model of bioelectric measurement system, under some simplified approximations.
This paper shows that some attempts are applied to the proposed method to improve the performance of fitting and eliminating the TMS artifact. One is to derive the strict solution of the TMS artifact by omitting some simplified approximations. Other is the countermeasure against errors calculating inverse matrix while estimat-ing parameters of fitting shape of the TMS artifact. One attempt is found that the strict solution improves the shape fitting but not so far from the approximated solu-tion. Other attempt improves stability of the simulation. These attempts are found that some time parameters which determine the time-transition such as “Tc” should separately treat against other time constant parameters which are derived from circuit parameters. Moreover, considering the residual component this is not described on the circuit model.
.
5. Yoshinori Katayama, Keiji Iramina, Equivalent Circuit Simulation of the Induced Artifacts Resulted from Transcranial Magnetic Stimulation on Human Electroencephalography, IEEE Trans. on Magnetics, Vol. 45, Issue 10, pp.4833 - 4836, 2009.10.
6. Takahiro Matsunaga, Tetsuya Fukuta, Yoshinori Katayama, Keiji Iramina, Analysis of evoked response and induced response in alpha wave and gamma wave during visual attention, Brain Topography and Multimodal Imaging,
Proceedings of the 18th International Congress on Brain Electromagnetic Topography
, 23-26, 2009.09.
7. Y.Katayama, S.Uchida, H.Sakoe , Stochastic Model of Stroke Order Variation, ICDAR 2009, pp.803-807, 2009.07.
8. 片山喜規,伊良皆啓治, 経頭蓋磁気刺激による脳波中の誘導ノイズアーチファクトのシミュレーションにおける生体等価回路, 日本生体磁気学会誌, Vol.21 No.2 pp.33-38, 2009.03.
9. Y.Katayama, S.Uchida, H.Sakoe, A New HMM for On-Line Character Recognition Using Pen-Direction and Pen-Coordinate Features, The 19th ICPR2008, CDROM, 2008.12.
10. 片山 喜規 内田 誠一 迫江 博昭, 座標特徴と方向特徴の選択的利用に基づくオンライン文字認識HMM, 電子情報通信学会論文誌. D-II, vol.J91-D, no.8, pp.2112-2120, Aug 2008, 2008.08.
11. 片山 喜規 内田 誠一 迫江 博昭, 筆順変動を表現するHMMとそのオンライン文字認識への応用, 電子情報通信学会論文誌. D-II, vol.J91-D, no.5, pp.1434-1441, May 2008, 2008.05.
12. 愼重弼、ムハマド マスルール アリ、片山喜規、迫江博昭, 画間相互情報を用いた筆順自由オンライン文字認識アルゴリズム, 電子情報通信学会, Vol.J82-D-II, No.3, pp.382-389, 1999.03.
主要学会発表等
1. Yuki Noguchi, Miki Kaneko, Keita Higashi, Yasushi Miyagi, R. Murayama, Keiji Iramina, Yoshinori Katayama, Evaluation for Treatment of Deep Brain Stimulation by Pronation and Supination of Forearms using Wireless Sensors
, 7th Biomedical Engineering International Conference (BMEiCON 2014), 2014.11.
2. Yoshinori Katayama, Yuki Noguchi, Miki Kaneko, Yasushi Miyagi, Keiji Iramina, Evaluation of DBS treatment against Parkinson's disease by the motion analysis of the pronation and supination of forearms, 第53回日本生体医工学会大会, 2014.06, Parkinson’s disease is said to be the excess output of basal ganglia (inhibitory system) which comes from the lack of dopamine by the degeneration of substantia nigra in the midbrain, and DBS (Deep Brain Stimulation) to the subthalamic nucleus is applied as the symptomatic treatment. This paper investigates the validation the effect of the DBS using the motion analysis of the pronation and supination of forearms. It needed the feature selection that reflects the change of the DBS on/off states and could evaluate the DBS effect quantitatively. The feature of the rotation angle had been found to be one of the suitable features which dynamically indicates a part of the motor function by investigating the change of the feature while DBS status was changed as off, on, and off again..
3. 片山 喜規, 伊良皆 啓治, TMS適用時の測定脳波に現れるTMSアーチファクト除去の為の等価回路モデル拡張
, 第51回日本生体医工学会大会, 2012.05, We have proposed a new method to eliminate the artifact induced on EEG when performing simultaneous measurement of EEG and transcranial magnetic stimulation (TMS). Because of its large amplitude compared to EEG, the TMS artifact should be reduced or eliminated. Our method is a unique parametric one based on modeling to describe and to eliminate TMS artifact on the measured EEG by fitting the solution function of the equivalent electric circuit models to the TMS artifact component. The proposed method basically separated the artifact from EEG.. Now we try to improve the fitting performance by extending the TMS artifact models against some TMS artifacts which have been difficult to fit ..
4. 片山喜規 伊良皆啓治 , モデル形状関数fittingによるTMSアーチファクト除去手法におけるモデル拡張の検討, 電子情報通信学会 MEとバイオサイバネティックス 研究会, 2012.01.
5. Yoshinori Katayama, Keiji Iramina, Development of Element Technology of Transcranial Magnetic Stimulation for Noninvasive Therapy, 日本磁気学会学術講演会, 2012.09.
6. Kazuhisa Nojima, Ge Shegn, Yoshinori Kataya, Keiji Iramina, Number of Pulses of rTMS affects the Inter-reversal Time of Perceptual Reversal, The 5th Kuala Lumpur International Conference on Biomedical Engineering, 8th Asian Pacific Conference on Medical and Biological Engineering (BioMed2011), 2012.06.
7. Y. Katayama K. Iramina, Fitting and Eliminating to the TMS Induced Artifact on the Measured EEG
by the Equivalent Circuit Simulation Improved Performance
, The 5th Kuala Lumpur International Conference on Biomedical Engineering, 8th Asian Pacific Conference on Medical and Biological Engineering (BioMed2011), 2012.06, Transcranial magnetic stimulation (TMS) is the non-invasive stimulus method to the brain by inducing the eddy current within the brain from the TMS coil placed outside the scalp. The induced eddy current stimulates the nerve circuit causes to suppress the brain activity partially in time and space, and it is applied to detect the brain functions etc. When TMS is applied to the brain while measuring the electroencephalography (EEG), the induced artifact caused by TMS covers on the EEG, it is called the TMS artifact. The amplitude of the TMS artifact is generally too large to omit diagnosing the EEG. Therefore some methods have been proposed to negate the TMS artifact from the EEG including the TMS artifact using the EEG only. We proposed a new method for describing the shape of the induced artifact in the EEG applied TMS using two equivalent circuit models, the TMS equipment model and the equivalent circuit model of bioelectric measurement system, under some simplified approximations.
This paper shows that some attempts are applied to the proposed method to improve the performance of fitting and eliminating the TMS artifact. One is to derive the strict solution of the TMS artifact by omitting some simplified approximations. Other is the countermeasure against errors calculating inverse matrix while estimat-ing parameters of fitting shape of the TMS artifact. One attempt is found that the strict solution improves the shape fitting but not so far from the approximated solu-tion. Other attempt improves stability of the simulation. These attempts are found that some time parameters which determine the time-transition such as “Tc” should separately treat against other time constant parameters which are derived from circuit parameters. Moreover, considering the residual component this is not described on the circuit model.
.
8. 片山喜規,伊良皆啓治, 回路モデルによるTMSアーチファクトの波形適合と除去の検討, 生体医工学会九州支部大会, 2011.01.
9. 片山喜規 ,伊良皆啓治, TMSアーチファクトの近似回路モデルシミュレーションの検討, マグネティックス/医用・生体工学合同研究会, 2010.11.
10. 片山喜規,伊良皆啓治, TMSアーチファクトの近似回路モデル表現とアーチファクト除去, 第25回 生体・生理工学シンポジウム(BPES2010), 2010.09.
11. 片山喜規,伊良皆啓治, TMSアーチファクトモデルと脳波信号処理, 電子情報通信学会 MEとバイオサイバネティックス研究会, 2010.01.
12. Takahiro Matsunaga, Yoshinori Katayama, Keiji Iramina, Analysis of evoked response and induced response in alpha wave and gamma wave during visual attention, 18th ISBET (International Congress on Brain Electromagnetic Topography), 2009.10.
13. 片山喜規. 伊良皆啓治, 経頭蓋磁気刺激が脳波に及ぼすアーチファクトのシミュレーション精度改善, 第62回電気関係学会九州支部連合大会, 2009.09.
14. Y.Katayama, K.Iramina, Equivalent Circuit Simulation of the Induced Artifacts Resulted from TMS on EEG, 11th International Congress of IUPESM World Congress 2009, 2009.09.
15. Y.Katayama, S.Uchida, H.Sakoe, Stochastic Model of Stroke Order Variation, ICDAR 2009, 2009.07.
16. Yoshinori Katayama, Keiji Iramina, Equivalent Circuit Simulation of the Induced Artifacts Resulted from Transcranial Magnetic Stimulation on Human Electroencephalography
, IEEE International Magnetics Conference 2009 (INTERMAG 2009), 2009.05.
17. 片山 喜規,伊良皆 啓治, 経頭蓋磁気刺激時脳波計測のノイズ除去の検討, 第48回日本生体医工学会大会, 2009.04.
18. 片山喜規,伊良皆啓治, TMSの脳波混入アーチファクトの電気回路モデル, 日本生体医工学会 専門別研究会 平成20年度第3回生体情報の可視化技術研究会, 2008.12.
19. Y.Katayama, S.Uchida, H.Sakoe , A New HMM for On-Line Character Recognition Using Pen-Direction and Pen-Coordinate Features, The 19th ICPR 2008, 2008.12.
20. 片山喜規 伊良皆啓治, 経頭蓋磁気刺激による脳波信号中の誘導ノイズアーチファクトのシミュレーション, 日本生体医工学会 専門別研究会 平成20年度第1回生体情報の可視化技術研究会, 2008.10.
21. 片山喜規 伊良皆啓治, 経頭蓋磁気刺激による脳波信号中の誘導アーチファクトのシミュレーション, 電気関係学会九州支部連合会, 2008.09.
22. 片山 喜規 内田 誠一 迫江 博昭, オンライン文字認識HMMにおける座標特徴と方向特徴の利用方法の検討, 電子情報通信学会 PRMU研究会, 2008.02.
23. Y.Katatama, S.Uchida, H.Sakoe, An Improved HMM for On-Line Handwriting Chinese Character Recognition using Pen-Coordinate and Pen-Direction Features, MPR2007 , 2007.11.
24. 渡邊偉志, 片山喜規, 内田誠一, 迫江博昭, オンライン文字認識HMMにおけるフック対策の検討, 九州支部大会, 2006.09.
25. 中野 正史 片山 喜規 迫江 博昭, キューブサーチのラジカル単位分解による高速化と高精度化の検討, 信学総大, 2000.03.
その他の優れた研究業績
2009.01, 学位取得(平成21年1月28日).
学会活動
所属学会名
電気学会
The Institute of Electrical and Electronics Engineers (IEEE)
電子情報通信学会
日本音響学会
学協会役員等への就任
2013.01~2013.10, 生体医工学シンポジウム2013 組織委員会, 委員(庶務、会計).
2012.04~2015.03, 電気学会 磁気を用いた新たなる診断・治療機器創出のための技術調査専門委員会, 幹事補佐.
学会大会・会議・シンポジウム等における役割
2011.09.26~2011.09.27, 電気関係学会九州支部連合大会, 座長(Chairmanship).
2010.11.22~2010.11.24, TENCON2010, 座長(Chairmanship).
2009.09.28~2009.09.29, 電気関係学会九州支部連合大会, 座長(Chairmanship).
2012.11.29~2012.11.29, 電気学会 マグネティックス研究会, 運営全般、会計.
2013.09.20~2013.09.21, 生体医工学シンポジウム2013, 組織委員会委員(庶務・会計・Web).
2013.03.21~2013.03.22, International Workshop on Biomedical Engineering: Focus on Interdisciplinary Education and Research, 運営、会計.
2012.11.16~2012.11.17, 電気学会 マグネティックス研究会, 運営全般、会計.
学術論文等の審査
年度 外国語雑誌査読論文数 日本語雑誌査読論文数 国際会議録査読論文数 国内会議録査読論文数 合計
2018年度
2017年度
2016年度
2015年度
2014年度
2013年度
2012年度 14 
2011年度
2010年度 14  26 
2009年度
2008年度
受賞
論文賞, 電子情報通信学会, 2009.05.
研究資金
科学研究費補助金の採択状況(文部科学省、日本学術振興会)
2009年度~2011年度, 基盤研究(B), 分担, リアルタイムコミュニケーション可能なアクティブBCIシステムの研究.
1998年度~1999年度, 萌芽的研究, 代表, 情報付与型HMMによる文字・図形認識システムの構築.
1998年度~2000年度, 基盤研究(C), 分担, 2次元パターンのワープ法に関する研究,分担.
1996年度~1997年度, 一般研究(C), 分担, 線図形画像直接構造解析法の高度化.
1992年度~1993年度, 一般研究(C), 分担, 神経回路モデル、確率モデルの適用によるオンライン文字認識の高度化に関する研究.
寄附金の受入状況
2010年度, 財団法人 磁気健康科学研究振興財団, 磁気健康科学研究振興財団 第16回研究助成/
経頭蓋磁気刺激が測定脳波に与える影響のシミュレーションと除去の実用化に関する研究.
学内資金・基金等への採択状況
2009年度~2009年度, 助教支援研究資金補助, 代表, BCIを指向した脳波信号処理方式の研究.

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