Hiroshi Higashi

Publications

Google Scholar Ciatation

Books and Book Chapters

  1. 東広志, 中西正樹, 田中聡久, 脳波処理とブレイン・コンピュータ・インタフェース —計測・処理・実装・評価の基礎—, コロナ社, 2022.
  2. H. Higashi and T. Tanaka, “Chapter 4: EEG signal processing with signal structures,” Signal Processing and Machine Learning for Brain-Machine Interfaces (T. Tanaka and M. Arvaneh Eds.), The Institution of Engineering and Technology, London, 2018.

Journal Papers

  1. H. Higashi, “Dimension-wise Sequential Update for Learning a Multidimensional Environment in Humans,” Journal of Cognitive Neuroscience, vol. 35, no. 5, pp. 841-855, 2023.
    DOI: 10.1162/jocn_a_01975
  2. K. Ito, H. Higashi, A. Hietanen, P. Fält, K. Hine, M. Hauta-Kasari, and S. Nakauchi, “The Optimization of the Light-Source Spectrum Utilizing Neural Networks for Detecting Oral Lesions,” Journal of Imaging, vol. 9, no. 1, p. 7, 2023.
    DOI: 10.3390/jimaging9010007 Open Access
  3. S. Nakauchi, T. Kondo, Y. Kinzuka, Y. Taniyama, H. Tamura, H. Higashi, K. Hine, T. Minami, J. M. M. Linhares, and S. M. C. Naschimento, “Universality and superiority in preference for chromatic composition of art paintings,” Scientific Reports, vol. 12, no. 4294, 2022.
    DOI: 10.1038/s41598-022-08365-z Open Access
  4. S. Nakakoga, H. Higashi, J. Muramatsu, S. Nakauchi, and T. Minami, “Asymmetrical characteristics of emotional responses to pictures and sounds: Evidence from pupillometry,” PLOS ONE, vol. 15, no. e0230775, 2020.
    DOI: 10.1371/journal.pone.0230775 Open Access
  5. T. Nishimoto, H. Higashi, H. Morioka, and S. Ishii, “An EEG-based personal identification method using unsupervised feature extraction and its robustness against intra-subject variability,” Journal of Neural Engineering, vol. 17, no. 026007, 2020.
    DOI: 10.1088/1741-2552/ab6d89 Open Access
  6. H. Higashi, M.V. Bui, A. Syahir, and S. Nakauchi, “Computational lighting for extracting optical features from RGB images,” Measurement, vol. 151, no. 107183, 2020.
    DOI: 10.1016/j.measurement.2019.107183
  7. H. Higashi, T. Minami, and S. Nakauchi, “Cooperative update of beliefs and state-transition functions in human reinforcement learning,” Scientific Reports, vol. 9, no. 17794, 2019.
    DOI: 10.1038/s41598-019-53600-9 Open Access
  8. T. Tamura, H. Higashi, and S. Nakauchi, “Dynamic visual cues for differentiating mirror and glass,” Scientific Reports, vol. 8, no. 8403, 2018.
    DOI: 10.1038/s41598-018-26720-x Open Access
  9. H. Higashi, T. Minami, and S. Nakauchi, “Variation in event-related potentials by state transitions,” Frontiers in Human Neuroscience, vol. 11, p. 75 (11 pages), 2017.
    DOI: 10.3389/fnhum.2017.00075 Open Access
  10. H. Higashi, T. M. Rutkowski, T. Tanaka, and Y. Tanaka, “Multilinear discriminant analysis with subspace constraints for single-trial classification of event-related potentials,” IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 7, pp. 1295–1305, 2016.
    DOI: 10.1109/JSTSP.2016.2599297 Open Access
    Python code
  11. H. Higashi, G. M. ElMasry, and S. Nakauchi, “Sparse regression for selecting fluorescence wavelengths for accurate prediction of food properties,” Chemometrics and Intelligent Laboratory Systems, vol. 154, pp. 29–37, 2016.
    DOI: 10.1016/j.chemolab.2016.03.008
  12. N. Tomida, T. Tanaka, S. Ono, M. Yamagishi, and H. Higashi, “Active data selection for motor imagery EEG classification,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 2, pp. 458–467, 2015.
    DOI: 10.1109/TBME.2014.2358536
  13. H. Higashi and T. Tanaka, “Common spatio-time-frequency patterns for motor-imagery based brain machine interfaces,” Computational Intelligence and Neuroscience, vol. 2013, Article ID 537218, 12 pages, 2013.
    DOI: 10.1155/2013/537218 Open Access
  14. Y. Kimura, T. Tanaka, H. Higashi, and N. Morikawa, “SSVEP-based brain-computer interfaces using FSK-modulated visual stimuli,” IEEE Transactions on Biomedical Engineering, vol. 60, no. 10, pp. 2831–2838, 2013.
    DOI: 10.1109/TBME.2013.2265260
  15. H. Higashi and T. Tanaka, “Simultaneous design of FIR filter banks and spatial patterns for EEG signal classification,” IEEE Transactions on Biomedical Engineering, vol. 60, no. 4, pp. 1100–1110, 2013.
    DOI: 10.1109/TBME.2012.2215960

Review Articles

  1. A. Bonci, S. Fiori, H. Higashi, T. Tanaka, and F. Verdini, “An introductory tutorial on brain–computer interfaces and their applications,” Electronics, vol. 10, no. 560, 2021.
    DOI: 10.3390/electronics10050560
  2. 田中聡久, 東広志, “非侵襲生体信号の処理と解析 –II– ブレイン・コンピュータ・インタフェース,” システム／制御／情報, vol. 62, no. 4, pp. 159-165, 2018.
    DOI: 10.11509/isciesci.62.4_159
  3. 東広志, 田中聡久, “信号構造を利用する脳波処理,” 計測と制御, vol. 55, no. 11, pp. 960–965, 2016.
    DOI: 10.11499/sicejl.55.960

International Conferences

  1. Z. Zhou, H. Higashi, and S. Ishii, “Data generation for missing frequencies in SSVEP-based brain computer interfaces,” The 19th Pacific Rim International Conference on Artificial Intelligence, Shanghai, Chaina, Nov., 2022.
  2. Z. Liang, H. Higashi, S. Oba, and S. Ishii, “Brain dynamics encoding from visual input during free viewing of natural videos,” International Joint Conference on Neural Networks 2019, Budapest, Hungary, p. N-19366, July, 2019.
  3. S. Nakakogao, H. Kajita, H. Higashi, S. Nakauchi, and T. Minami, “Puplillary changes reflect visual spatial attention modualated by emotional sounds,” European Conference on Visual Perception 2018, Trieste, Italy, Aug., 2018.
  4. Y. Nihei, H. Higashi, T. Minami, and S. Nakauchi, “Rapid categorization of face-like objects in a fast-periodic visual stimulation,” European Conference on Visual Perception 2018, Trieste, Italy, Aug., 2018.
  5. S. Nakuchi, T. Kondo, H. Higashi, M.M.J. Linhares, M.C.S. Nascimento, “Color statistics underlying preference judgement for art paintings,” The 18th Annual Meeting of the Vision Sciences, Florida, USA, May, 2018.
  6. T. Kondo, N. Okada, K. Maruchi, Y. Misaki, H. Higashi, J. AR Monteiro, C. Montagner, J. MM Linhares, S. MC Nascimento, S. Nakauchi, “Chromatic composition and preferences of paintings — Comparative study for Japanese and Portuguese observers and paintings,” The 24th symposium of the International Colour Vision Society, Berlin, Germany, Aug., 2017.
  7. H. Tamura, H. Higashi, and S. Nakauchi, “Multiple cues for visual perception of mirror and glass materials,” The 17th Annual Meeting of the Vision Sciences, Florida, USA, May, 2017.
  8. S. Nakauchi, K. Shiromi, H. Higashi, M. Shehata, and S. Shimojo, “Luminance-contrast reversal disambiguates illumination interpretation in #TheDress,” The 17th Annual Meeting of the Vision Sciences, Florida, USA, May, 2017.
  9. H. Higashi, T. M. Rutkowski, T. Tanaka, and Y. Tanaka, “Smoothing of xDAWN spatial filters for robust extraction of event-related potentials,” in Proceedings of The 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2016), pp. 1–5, Jeju, Korea, Dec. 2016.
    DOI: 10.1109/APSIPA.2016.7820750
  10. T. Kondo, J. L. Nieves, E. M. Valero, H. Higashi, and S. Nakauchi, “Functional illumination supporting the visual detection of plaques,” in Proceedings of IS&T 24th Color Imaging Conference (CIC 24), pp. 219–224, San Diego, USA, Nov. 2016.
    DOI: 10.2352/ISSN.2169-2629.2017.32.219
  11. H. Tamura, H. Higashi, and S. Nakauchi, “Kinetic cue perceptual discrimination between mirror and glass,” European Conference on Visual Perception, Barcelona, Spain, Aug. 2016.
  12. K. Ito, H. Higashi, and S. Nakauchi, “A visualization method for hand cleanness using fluorescent spectrum,” in Proceedings of The 2016 International Conference on Advanced Informatics: Concepts, Theory and Applications, pp. 1–5, Penang, Malaysia, Aug. 2016.
    DOI: 10.1109/ICAICTA.2016.7803096
  13. T. Kondo, H. Higashi, and S. Nakauchi, “Optimization of illuminant spectrum for visual detection of foreign substances in jams,” in Proceedings of The 2016 International Conference on Advanced Informatics: Concepts, Theory and Applications, pp. 1–4, Penang, Malaysia, Aug. 2016.
    DOI: 10.1109/ICAICTA.2016.7803123
  14. S. Ryu, H. Higashi, T. Tanaka, S. Nakauchi, and T. Minami, “Spatial smoothing of canonical correlation analysis for steady state evoked potential based brain computer interfaces,” in Proceedings of 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016), pp. 1516–1519, Florida, USA, Aug. 2016.
    DOI: 10.1109/EMBC.2016.7590998
  15. Y. Suzuki, T. Shinkai, H. Higashi, T. Minami and S. Nakauchi, “Mismatch between perception and neural response in glare illusion,” The 16th Annual Meeting of the Vision Sciences, Florida, USA, May, 2016.
  16. H. Tamura, M. Tsukuda, H. Higashi, and S. Nakauchi, “Perceptual segregation between mirror and glass material under natural and unnatural illumination,” The 16th Annual Meeting of the Vision Sciences, Florida, USA, May, 2016.
  17. H. Higashi,, T. M. Rutkowski, T. Tanaka, and Y. Tanaka, “Subspace-constrained multilinear discriminant analysis for ERP-based brain computer interface classification,” in Proceedings of The 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2015), pp. 934–940, Hong Kong, China, Dec. 2015.
    DOI: 10.1109/APSIPA.2015.7415409
  18. K. Ito, Yuki Ota, H. Higashi, and S. Nakauchi, “Spectral-difference enhancing illuminant for improving visual detection of blood vessels,” in Proceedings of The 2015 International Conference on Advanced Informatics: Concepts, Theory and Applications, Chonburi, Thailand, Aug. 2015.
    DOI: 10.1109/ICAICTA.2015.7335377
  19. Y. Ota, H. Higashi, and S. Nakauchi “Objective assessment and qualification of pearl quality by spectral-spatial features,” in Proceedings of The 2015 International Conference on Advanced Informatics: Concepts, Theory and Applications, Chonburi, Thailand, Aug. 2015.
    DOI: 10.1109/ICAICTA.2015.7335372
  20. H. Higashi, T. Minami, S. Nakauchi “Classification of electroencephalogram under different process of stimulus occurrences in an oddball paradigm,” in Proceedings of International Conference of Global Network for Innovative Technology 2014, Penang, Malaysia, Dec. 2014.
  21. H. Higashi, T. Tanaka, and Y. Tanaka “Smoothing of spatial filter by graph Fourier transform for EEG signals,” in Proceedings of The 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2014), pp. 1–8, Siem Reap, Cambodia, Dec. 2014.
    DOI: 10.1109/APSIPA.2014.7041710
  22. H. Higashi and T. Tanaka, “Band selection by distance of spatial patterns for brain machine interfacing,” in Proceedings of The 2014 International Conference on Advanced Informatics: Concepts, Theory and Applications, pp. 63–68, Bandung, Indonesia, Aug. 2014.
    DOI: ICAICTA.2014.7005916
  23. H. Higashi and T. Tanaka, “Band selection by criterion of common spatial patterns for motor imagery based brain machine interfaces,” in Proceedings of The 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2013), pp. 1–7, Kaohsiung, Taiwan, Oct. 2013.
    DOI: 10.1109/APSIPA.2013.6694273
  24. H. Higashi and T. Tanaka, “Regularization using similarities of signals observed in nearby sensors for feature extraction of brain signals,” in Proceedings of 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), pp. 7420–7423, Osaka, Japan, Jul. 2013.
    DOI: 10.1109/EMBC.2013.6611273
  25. N. Tomida, H. Higashi, T. Tanaka, “A joint tensor diagonalization approach to active data selection for EEG classification,” in Proceedings of 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), pp. 983–987, Vancouver, Canada, May. 2013.
    DOI: 10.1109/ICASSP.2013.6637796
  26. S. Yoshimoto, Y. Washizawa, T. Tanaka, H. Higashi, J. Tamura, “Toward multi-command auditory brain computer interfacing using speech stimuli,” in Proceedings of APSIPA Annula Summit and Conference 2012 (APSIPA ASC 2012), pp. 1–4, Hollywood, USA, Dec. 2012.
  27. H. Higashi and T. Tanaka, “Time sparsification of EEG signals in motor-imagery based brain computer interfaces,” in Proceedings of 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2012), pp. 4271–4274, San Diego, USA, Aug. 2012.
    DOI: 10.1109/EMBC.2012.6346910
  28. C. Zhang, Y. Kimura, H. Higashi, and T. Tanaka, “A simple plat form of brain-contralled mobile robot and its implementation by SSVEP,” in Proceedings of 2012 International Joint Conference on Neural Networks (IJCNN 2012), pp. 1–7, Brisbane, Australia, Jun. 2012.
    DOI: 10.1109/IJCNN.2012.6252579
  29. H. Higashi, A. Cichocki, and T. Tanaka, “Regularization using geometric information between sensors capturing features from brain signals,” in Proceedings of 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), pp. 721–724, Kyoto, Japan, Mar. 2012.
    DOI: 10.1109/ICASSP.2012.6287985
  30. L. Zhang, C. Zhang, H. Higashi, J. Cao, and T. Tanaka, “Common spatial pattern using multivariate EMD for EEG classification,” in Proceedings of The 2011 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2011), Wed-PM. SS4 (5 pages), Xi’an, China, Oct. 2011.
  31. H. Higashi and T. Tanaka, “Optimal design of a bank of spatio-temporal filters for EEG signal classification,” in Proceedings of 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp. 6100–6103, Boston, USA, Sept. 2011.
    DOI: 10.1109/IEMBS.2011.6091507
  32. H. Higashi, T. M. Rutkowski, Y. Washizawa, A. Cichocki, and T. Tanaka, “EEG auditory steady state responses classification for the novel BCI,” in Proceedings of 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp. 4576–4579, Boston, USA, Sept. 2011.
    DOI: 10.1109/IEMBS.2011.6091133
  33. H. Higashi and T. Tanaka, “Classification by weighting for spatio-frequency components of EEG signal during motor imagery,” in Proceedings of 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2011), pp. 585–588, Prague, Czech Republic, May 2011.
    DOI: 10.1109/ICASSP.2011.5946471
  34. Y. Washizawa, H. Higashi, T. M. Rutkowski, T. Tanaka, and A. Cichocki, “Tensor based simultaneous feature extraction and sample weighting for EEG classification,” Lecture Notes in Computer Science, vol. 6444, pp. 26–33, 17th International Conference on Neural Information Processing (ICONIP 2010), Sydney, Australia, Nov. 2010.
    DOI: 10.1007/978-3-642-17534-3_4
  35. H. Higashi, T. Tanaka, and Y. Mitsukura, “Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing,” in Proceedings of 2010 International Joint Conference on Neural Networks (IJCNN 2010), pp. 3508–3513, Barcelona, Spain, Jul. 2010.
    DOI: 10.1109/IJCNN.2010.5596476
  36. T. Tanaka, H. Higashi, and Y. Saito, “Rhythmic component extraction for EEG signals with reduced computational complexity,” in Proceedings of 2009 IEEE International Symposium on Biomedical Engineering (ISBME 2009), no. 1054, Bangkok, Thailand, Dec. 2009.
  37. H. Higashi, T. M .Rutkowski, Y. Washizawa, T. Tanaka, and A. Cichocki, “Imagery movement paradigm user adaption improvement with quasi-movement phenomenon,” Advances in Cognitive Neurodynamics (II), pp. 683–688, The 2nd International Conference on Cognitive Neurodynamics (ICCN 2009), Hangzshou, China, Nov. 2009.
  38. H. Higashi, T. Tanaka, and A. Funase, “Classification of single trial EEG during imagined hand movement by rhythmic component extraction,” in Proceedings of 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), pp. 2482–2485, Minneapolis, USA, Sept. 2009.
    DOI: 10.1109/IEMBS.2009.5334806
  39. Y. Saito, T. Tanaka, and H. Higashi, “Adaptive rhythmic component extraction with regularization for EEG data analysis,” in Proceedings of 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009), pp. 353–356, 2009.
    DOI: 10.1109/ICASSP.2009.4959593

国内会議

  1. 東広志, Bui Minh Vu, Aziz Ahmad Syahir, 中内茂樹, “RGB画像を用いた光学的特徴抽出のための照明最適化,” 照明学会第52回全国大会, p. 3-O-01, 福岡, 2019年9月.
  2. 東広志, Bui Minh Vu, Aziz Ahmad Syahir, 中内茂樹, “RGB画像からの光学的特徴抽出のための最適照明の教師あり学習,” 電子情報通信学会第33回信号処理シンポジウム, pp. 81–86, 東京, 2018年11月.
  3. 近藤泰成, 東広志, Sergio M.C. Nascimento, 中内茂樹, “絵画の色彩選好におけるポルトガル人と日本人の類似性と相違点,” 第5回多元質感知領域班会議, p. 46, 東京, 2018年3月
  4. 近藤泰成, 東広志, Sergio M.C. Nascimento, 中内茂樹, “絵画の色彩選好におけるユニバーサリティーと色彩統計量,” 質感のつどい第3回公開フォーラム, p. 28, 大阪, 2017年11月
  5. 中内茂樹, 白見海, 東広志, Mohammad Shehata, 下條信輔, “輝度反転による#TheDressの照明解釈の曖昧性の消失,” 質感のつどい第3回公開フォーラム, p. 32, 大阪, 2017年11月
  6. 中古賀理, 東広志, 村松潤哉, 中内茂樹, 南哲人, “瞳孔計測を用いたヒトの情動状態の評価,” ヒューマンインフォメーション研究会, pp. 93–96, 京都, 2017年10月
  7. 龍進吾, 東広志, 村松潤哉, 中内茂樹, 南哲人, “情動誘発画像を用いたEEG・NIRS信号の分類,” ヒューマンインフォメーション研究会, pp. 39–42, 京都, 2017年10月
  8. 中島健太, 南哲人, 東広志, 中内茂樹, “周辺視野における刺激周波数とSSVEP応答の関係,” ヒューマンインフォメーション研究会, pp. 35–38, 京都, 2017年10月
  9. 中内茂樹, 近藤泰成, 東広志, Sergio M.C. Nascimento, , “絵画に対する選好に見られるポルトガル人と日本人の類似性と相違点,” 日本認知科学会第34回大会 金沢, 2017年9月
  10. 近藤泰成, 三崎幸典, 東広志, Sergio M.C. Nascimento, 中内茂樹, “絵画の色彩選好に対する文化依存性とユニバーサリティー,” 日本視覚学会2017夏季大会, 島根, 2017年9月
  11. 近藤泰成, 東広志, Sergio M.C. Nascimento, 中内茂樹, “絵画の色彩選好におけるポルトガル人と日本人の類似性と相違点,” 第4回多元質感知領域班会議, 宮城, 2017年6月
  12. 田村秀樹, 東広志, 中内茂樹, “運動情報に潜む鏡面反射・透過情報,” 第3回多元質感知領域班会議, 東京, 2017年3月
  13. 伊藤和哉, 東広志, 中内茂樹, “蛍光特性に基づく手の汚染分布可視化,” 日本色彩学会視覚情報基礎研究会第30回研究発表会, 千葉, 2017年2月.
  14. 田村秀樹, 東広志, 中内茂樹, “鏡・ガラス材質を識別するための複数の視覚手がかり,” 日本視覚学会2017冬季大会, 東京, 2017年1月.
  15. 近藤泰成, J. L. Nieves, E. M. Valero, 東広志, 中内茂樹, “プラーク検出を補助する機能性光源,” 日本色彩学会視覚情報基礎研究会第29回研究発表会, pp. 21–24, 東京, 2016年12月.
  16. 田村秀樹, 東広志, 中内茂樹, “回転運動物体に対する鏡・ガラス材質の知覚,” 質感のつどい第2回公開フォーラム, 千葉, 2016年11月.
  17. 東広志, “チャンネル間の連結度を利用した脳波アーチファクト除去,” 電子情報通信学会第31回信号処理シンポジウム, pp. 103–104, 2016年11月.
  18. 龍進吾, 東広志, 中内茂樹, 南哲人, “電極配置情報を利用した正準相関分析による定常状態視覚誘発電位の識別,” 第39回日本神経科学大会, 神奈川, 2016年7月.
  19. 田村秀樹, 東広志, 中内茂樹, “鏡・ガラス材質識別に関わる動的情報,” 第2回多元質感知領域班会議, シーガイアコンベンションセンター, 宮崎, 2016年6月
  20. 田村秀樹, 佃将樹, 東広志, 中内茂樹, “鏡・ガラス材質識別に関わる視覚的手がかりと照明場依存性,” 第1回多元質感知領域班会議, 広島国際会議場・広島市立大学, 広島, 2016年1月
  21. 東広志, Tomasz M. Rutkowski, 田中聡久, 田中雄一, “部分空間制約を用いた多次元線形判別法による単一試行事象関連電位の識別,” 電子情報通信学会第30回信号処理シンポジウム, pp. 396–397, 福島, 2015年11月.
  22. 東広志, 田中聡久, 田中雄一, “グラフスペクトルを用いた制約付き脳波処理,” 第54回生体医工学会, 名古屋, 2015年5月.
  23. 東広志, 南哲人, 中内茂樹, “事象関連電位を用いた刺激の条件付き発生確率推定,” 電子情報通信学会第29回信号処理シンポジウム, 京都, 2014年11月.
  24. 東広志, 田中聡久, “運動想像脳波識別のための空間パターンの類似性による帯域選択,” 電子情報通信学会第28回信号処理シンポジウム, pp. 485–486, 下関, 2013年11月.
  25. 田中聡久, 冨田尚規, 東広志, “脳波クラス分類のための疎性による能動的データ選択法,” 信学技報, vol. 113, no. 191, SIP2013-84, pp. 97–102, 東京, 2013年8月.
  26. 冨田尚規, 東広志, 田中聡久, “テンソル同時対角化によるサンプルの重み付けを用いた脳波識別,” 信学技報, vol. 112, no. 423, SIP2012-107, pp. 153–158, 広島, 2013年1月.
  27. 東広志, 田中聡久, “脳波識別のためのフィルタバンク・空間重み・時間窓の最適設計,” 電子情報通信学会第27回信号処理シンポジウム, pp. 235–240, 沖縄, 2012年11月.
  28. 東広志, 田中聡久, “運動想起中の脳波識別における時間窓のスパース化,” 信学技報, vol. 112, no. 115, SIP2012-34, pp. 7–12, 京都, 2012年7月.
  29. 田村潤, 鷲沢嘉一, 東広志, 森川直樹, 田中聡久, “音声刺激による聴覚ブレイン・コンピュータ・インターフェイスの可能性,” 信学技報, vol. 111, no. 466, SIP2011-177, pp. 281–286, 新潟, 2012年3月.
  30. 木村陽介, 東広志, 田中聡久, “FSK変調した視覚刺激によるBCI,” 信学技報, vol. 111, no. 315, NC2011-80, pp. 47–52, 宮城, 2011年11月.
  31. 張誠, 木村陽介, 東広志, 田中聡久, “An SSVEP-Based BCI to Control a Mobile Robot via the Internet,” 信学技報, vol. 111, no. 315, NC2011-79, pp. 41–46, 2011年11月.
  32. 張誠, 木村陽介, 東広志, 田中聡久, “Control of a Mobile Robot via Wi-Fi with an SSVEP-Based BCI,” 電子情報通信学会第26回信号処理シンポジウム, pp. 602–607, 北海道, 2011年11月.
  33. 東広志, Andrzej Cichocki, 田中聡久, “脳波電極間の距離情報を用いた正則化,” 電子情報通信学会第26回信号処理シンポジウム, pp. 497–502, 北海道, 2011年11月.
  34. 東広志, 田中聡久, “脳波識別のための時空間フィルタバンクの最適設計,” 信学技報, vol. 111, no. 102, SIP2011-44, pp. 85–90, 沖縄, 2011年6月.
  35. 木村陽介, 東広志, 田中聡久, “定常的視覚誘発電位を用いたディジタル通信,” 2011年 電子情報通信学会総合大会 基礎・境界講演論文集, A-4-27, pp. 105, 2011年3月.
  36. 東広志, 田中聡久, “運動想像時脳波識別のためのFIRフィルタ設計法,” 2011年 電子情報通信学会総合大会 基礎・境界講演論文集, A-4-34, p. 112, 2011年3月.
  37. 東広志, 鷲沢嘉一, T. Rutkowski, 田中聡久, A. Cichocki, “定常的聴覚誘発電位を用いた脳コンピュータインターフェイス,” 信学技報, vol. 110, No. 368, SIP2010-106, pp. 221–226, 鹿児島, 2011年1月.
  38. 東広志, 田中聡久, “運動想像時脳波の空間-周波数成分の重み付けによる識別,” 電子情報通信学会第25回信号処理シンポジウム, pp. 121–126, 奈良, 2010年11月.
  39. 東広志, 田中聡久, “脳コンピュータインターフェイスのための位相を用いた律動成分抽出法,” 電子情報通信学会第24回信号処理シンポジウム, pp. 402–407, 鹿児島, 2009年11月.
  40. 木村陽介, 東広志, 田中聡久， “BCIのための律動成分抽出を用いた定常的視覚誘発電位の観測法,” 信学技報, NC2009-54, pp. 23–28, 宮城, 2009年11月.
  41. 田中聡久, 斎藤祐樹, 東広志, “律動成分分析の適応高速アルゴリズムに関する一検討,” 信学技報, SIP2009-27, pp. 49–53, 北海道, 2009年6月.
  42. 斎藤祐樹, 田中聡久, 東広志, “適応律動成分抽出法と脳波解析への応用,” 電子情報通信学会第23回信号処理シンポジウム, pp. 58–63, 宮城, 2008年11月.

Thesis