Updated on 2022/06/30

写真a

 
SHIBANOKI Taro
 
Organization
Faculty of Natural Science and Technology Associate Professor
Position
Associate Professor
External link

Degree

  • D.Eng. ( Hiroshima University )

Research Areas

  • Life Science / Medical systems  / Medical Systems

  • Life Science / Rehabilitation science  / Rehabilitation Science/Welfare Engineering

Education

  • Hiroshima University   大学院工学研究科 博士課程後期  

    - 2012.9

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  • Hiroshima University   大学院工学研究科 博士課程後期  

    - 2012.9

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  • The University of Tokushima   工学部  

    - 2008.3

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Research History

  • Okayama University   The Graduate School of Natural Science and Technology   Associate Professor

    2021.4

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  • Associate Professor, Graduate School of Science and Engineering, Ibaraki University

    2020.4 - 2021.4

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  • Lecturer, College of Engineering, Ibaraki University

    2016.4 - 2020.3

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  • 茨城キリスト教大学・兼任講師

    2015.4 - 2018.3

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  • Assistant Professor, College of Engineering, Ibaraki University

    2014.4 - 2016.3

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  • Assistant Professor (Special Appointment), Institute of Engineering, Hiroshima University

    2013.4 - 2014.3

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  • JSPS Research Fellow (PD)

    2012.10 - 2013.3

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  • JSPS Research Fellow (PD)

    2012.10 - 2013.3

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  • JSPS Research Fellow (DC2)

    2011.4 - 2012.9

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  • JSPS Research Fellow (DC2)

    2011.4 - 2012.9

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Professional Memberships

Committee Memberships

  • SCI'21   実行委員  

    2021   

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  • International Conference on Artificial Life and Robotics   Program Committee  

    2020   

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  • 第26回ロボティクスシンポジア/第26回ロボティクスシンポジア 特集号   実行委員/ゲストアソシエートエディタ  

    2019 - 2021   

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  • 日本ロボット学会   会誌編集委員  

    2017.3 - 2019.3   

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  • 計測自動制御学会   システムインテグレーション(SI)部門ロボティクス部会委員  

    2017   

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Papers

  • Effects of Tactile Stimulation Near the Auricle on Body Sway Reviewed

    Masaya Tadokoro, Taro Shibanoki

    Journal of Robotics and Networking and Artificial Life   9 ( 1 )   2022

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  • Relationship Between Tactile Stimuli and Human Body Sway Reviewed

    Masaya Tadokoro, Taro Shibanoki

    588 - 591   2021.1

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  • A 3D-printable Prosthetic Hand Based on a Dual-arm Operation Assistance Model Reviewed

    Taro Shibanoki, Kosuke Jin

    Proceedings of 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech 2021)   137 - 138   2021

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  • A Neural Network Based on the Johnson SU Translation System and Related Application to Electromyogram Classification Reviewed

    Hideaki Hayashi, Taro Shibanoki, Toshio Tsuji

    IEEE Access   9   154304 - 154317   2021

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/access.2021.3126348

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  • An EMG-controlled Mobile Robot Based on a Multi-layered Non-contact Impedance Model Reviewed

    Taro Shibanoki, Masaru Sasaki, Toshio Tsuji

    130 - 131   2021

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  • Longitudinal assessment of U-shaped and inverted U-shaped developmental changes in the spontaneous movements of infants via markerless video analysis Reviewed

    Naoki Kinoshita, Akira Furui, Zu Soh, Hideaki Hayashi, Taro Shibanoki, Hiroki Mori, Koji Shimatani, Yasuko Funabiki, Toshio Tsuji

    Scientific Reports   10 ( 16827 )   2020.10

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    <title>Abstract</title>
    Various attempts have been made to elucidate the development patterns in the spontaneous movements of infants through longitudinal evaluations. Movement complexity has been found to demonstrate u-shaped changes in the measurements focusing on limb movements. However, researchers have not yet clarified how other characteristics, besides movement complexity, change over time. This paper presents a longitudinal evaluation of spontaneous movements in infants using evaluation indices calculated through markerless video analysis. Nine infants with corrected ages from <inline-formula><alternatives><tex-math>$$-1$$</tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
    <mml:mrow>
    <mml:mo>-</mml:mo>
    <mml:mn>1</mml:mn>
    </mml:mrow>
    </mml:math></alternatives></inline-formula> to 15 weeks participated in the experiments. We confirmed the change in indices over time using statistical methods. Index changes can be classified as positively correlated, u-shaped, inverted u-shaped, and uncorrelated. We also confirmed that the u-shaped and inverted u-shaped indices are negatively correlated. Furthermore, the principal component analysis revealed that the first principal component had the inverted u-shaped changes with the corrected age. These results suggest that it is important to synchronize the inverted u-shaped variations in the movement and velocity with the u-shaped changes in the movement complexity for infant development.

    DOI: 10.1038/s41598-020-74006-y

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    Other Link: http://www.nature.com/articles/s41598-020-74006-y

  • A 3D-printable Prosthetic Hand Considering Dual-arm Operation Reviewed

    Taro Shibanoki, Kosuke Jin

    Proceedings of 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2020), pp. 262-263, Kyoto, March 10-12, 2020.   262 - 263   2020.3

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  • A Training System for Brain-Computer Interfaces Based on Motor Imagery Selection Reviewed

    Yuki Koizumi, Taro Shibanoki, Toshio Tsuji

    Proceedings of 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2020), pp. 217-218, Kyoto, March 10-12, 2020.   217 - 218   2020.3

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  • A New Approach for Training on EMG-based Prosthetic Hand Control Reviewed

    Taro Shibanoki, Kazuya Hashimoto, Go Nakamura, Takaaki Chin, Toshio Tsuji

    Proceedings of 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2020), pp. 307-308, Kyoto, March 10-12, 2020.   307 - 308   2020.3

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  • Markerless Measurement and Evaluation of General Movements in Infants. Reviewed International journal

    Toshio Tsuji, Shota Nakashima, Hideaki Hayashi, Zu Soh, Akira Furui, Taro Shibanoki, Keisuke Shima, Koji Shimatani

    Scientific reports   10 ( 1422 )   2020.1

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    General movements (GMs), a type of spontaneous movement, have been used for the early diagnosis of infant disorders. In clinical practice, GMs are visually assessed by qualified licensees; however, this presents a difficulty in terms of quantitative evaluation. Various measurement systems for the quantitative evaluation of GMs track target markers attached to infants; however, these markers may disturb infants' spontaneous movements. This paper proposes a markerless movement measurement and evaluation system for GMs in infants. The proposed system calculates 25 indices related to GMs, including the magnitude and rhythm of movements, by video analysis, that is, by calculating background subtractions and frame differences. Movement classification is performed based on the clinical definition of GMs by using an artificial neural network with a stochastic structure. This supports the assessment of GMs and early diagnoses of disabilities in infants. In a series of experiments, the proposed system is applied to movement evaluation and classification in full-term infants and low-birth-weight infants. The experimental results confirm that the average agreement between four GMs classified by the proposed system and those identified by a licensee reaches up to 83.1 ± 1.84%. In addition, the classification accuracy of normal and abnormal movements reaches 90.2 ± 0.94%.

    DOI: 10.1038/s41598-020-57580-z

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  • A Training Method for Voice Signal-based Human Interfaces Based on False Recognition Invited Reviewed

    Taro Shibanoki, Go Nakamura, Takaaki Chin, Toshio Tsuji

    The SICE Annual Conference 2019 (SICE 2019)   48 - 49   2019

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  • A Dual-arm Cooperation Training System for Myoelectric Prosthetic Hand Control Reviewed

    Kazuya Hashimoto, Taro Shibanoki, Go Nakamura, Takaaki Chin, Toshio Tsuji

    The Second Annual IEEE Life Sciences Conference (LSC), 2pages, Montreal, Canada, 28-30 October, 2018.   2018.10

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  • Selection of Motor Imagries for Brain–Computer Interfaces Based on Partial Kullback–Leibler Information Measure Reviewed

    Taro Shibanoki, Yuki Koizumi, Bi Adriel, Jr. Yozan, Toshio Tsuji

    The Second Annual IEEE Life Sciences Conference (LSC), pp. 243-246, Montreal, Canada, 28-30 October, 2018.   2018.10

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  • A Training Method for the Speech Controlled Environmental Control System Based on Candidate Word Discriminations Reviewed

    Taro Shibanoki, Masaki Watanabe, Go Nakamura, Takaaki Chin, Toshio Tsuji

    Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018), pp. 135-138   2018.9

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  • An EMG-based Prosthetic Hand Training System Using a Class Partial Kullback-Leibler Information Reviewed

    Tai Tomizawa, Taro Shibanoki, Takaaki Chin, Toshio Tsuji

    The first IEEE Life Sciences Conference (LSC2017), Sydney, December 13-15, 2017   2017.12

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  • A virtual myoelectric prosthesis training system capable of providing instructions on hand operations Reviewed

    Go Nakamura, Taro Shibanoki, Yuichi Kurita, Yuichiro Honda, Akito Masuda, Futoshi Mizobe, Takaaki Chin, Toshio Tsuji

    International Journal of Advanced Robotic Systems   14 ( 5 )   2017

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    © The Author(s) 2017. This article proposes a virtual hand and a virtual training system for controlling the MyoBock—the most commonly used myoelectric prosthetic hand worldwide. As the virtual hand is controlled using the method also adopted for the MyoBock hand, the proposed system provides upper-limb amputees with operation sensibilities similar to those experienced in MyoBock control. It can also display an additional virtual hand for the provision of instructions on hand operation, such as the recommended posture for object grasping and the trajectory desirable to reach a target. In virtual hand control experiments conducted with an amputee to evaluate the proposed virtual hand’s operability, the subject successfully performed stable opening and closing with high discrimination rates (89:3±6:65%), thanks to the virtual hand’s incorporation of the MyoBock’s operational characteristics. A training experiment using the proposed system was also conducted with eight healthy participants over a period of 5 days. The participants were asked to perform the box and block test using the MyoBock hand in a real environment on the first and final days. The results showed that the number of blocks transported in 1 min significantly increased and that the participants using the instruction virtual hand changed the orientation of the hand approaching blocks from vertical to lateral. The outcomes of the experiment indicate that the proposed system can be used to improve MyoBock hand control operation both quantitatively and qualitatively.

    DOI: 10.1177/1729881417728452

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  • Obstacle Avoidance Method for Electric Wheelchairs Based on a Multi-Layered Non-Contact Impedance Model Reviewed

    Haruna Kokubo, Taro Shibanoki, Takaaki Chin, Toshio Tsuji

    Journal of Robotics, Networking and Artificial Life, vol. 4, issue 1   45 - 48   2017

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  • A Voice Signal-Based Manipulation Method for the Bio-Remote Environment Control System Based on Candidate Word Discriminations Reviewed

    Taro Shibanoki, Go Nakamura, Takaaki Chin, Toshio Tsuji

    Journal of Robotics, Networking and Artificial Life, vol. 4, issue 1   87 - 90   2017

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  • A Virtual Myoelectric Prosthesis Training System Capable of Providing Instructions on Hand Operations Reviewed

    Go Nakamura, Taro Shibanoki, Yuichi Kurita, Yuichiro Honda, Akito Masuda, Futoshi Mizobe, Takaaki Chin, Toshio Tsuji

    International Journal of Advanced Robotic Systems, Vol. 14, Issue 5, DOI: 10.1177/1729881417728452 (10 pages)   2017

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  • A human reaching movement model for Myoelectric Prosthesis Control Reviewed

    Go Nakamura, Taro Shibanoki, Yuichiro Honda, Futoshi Mizobe, Akito Masuda, Takaaki Chin, Toshio Tsuji

    Journal of Robotics, Networking and Artificial Life, vol. 4, issue 1   22 - 27   2017

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  • A Body Sway Mitigation Method Based on Tactile Stimulation Reviewed

    Satowa Watanabe, Taro Shibanoki, Koji Shimatani

    The SICE Annual Conference 2016 (SICE2016)   518 - 519   2016.9

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  • A High-fidelity Virtual Training System for Myoelectric Prostheses Using an Immersive HMD Reviewed

    Go Nakamura, Taro Shibanoki, Futoshi Mizobe, Akito Masuda, Yuichiro Honda, Takaaki Chin, Toshio Tsuji

    Proceedings of 10th international Convention on Rehabilitation Engineering & Assistive Technology (i-CREATe2016), Thailand, July 25-28, 2016   PP5.2   2016.7

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  • An Interactive Training System for Myoelectric Prostheses using Virtual Hand Reviewed

    Shibanoki Taro, Tsuji Toshio, Nakamura Go, Orihashi Fuminori, Hayashi Hideaki, Kurita Yuichi, Takaki Takeshi, Honda Yuichiro, Mizobe Futoshi, Chin Takaaki

    Journal of the Robotics Society of Japan   34 ( 6 )   404 - 410   2016

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Robotics Society of Japan  

    This paper proposes an interactive training system for control of myoelectric prostheses. The proposed training system is capable of selecting suitable motions (EMG patterns) for each user by eliminating ineffective ones, and can also provide consistency between user's motor images and the corresponding prosthetic movements using a virtual prosthetic hand (VH). In the experiments performed, a one-day training session using the proposed system was conducted with nine healthy males (including an experienced) and an upper limb amputee. In addition, EMG discrimination ability of each subject during VH control without any feedback information was evaluated before and after the training to verify the training effects of the proposed system. The results showed that the discrimination rates for selected motions were sufficiently high (98.9 &plusmn; 1.24%) by using the proposed selection method, and the accuracy in discrimination for VH control was significantly improved after training (for healthy subjects and the amputee at the 0.1% and 1% level, respectively). It is therefore confirmed that the proposed system can be used for myoelectric prosthesis control training.

    DOI: 10.7210/jrsj.34.404

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  • A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis Reviewed

    Hideaki Hayashi, Taro Shibanoki, Keisuke Shima, Yuichi Kurita, Toshio Tsuji

    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS   26 ( 12 )   3021 - 3033   2015.12

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    This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

    DOI: 10.1109/TNNLS.2015.2400448

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  • Development of the Bio-Remote Adaptive Human Interface with Novel Glasses-based Operation Reviewed

    Go Nakamura, Akitoshi Sugie, Taro Shibanoki, Keisuke Shima, Yuichi Kurita, Yuichiro Honda, Takaaki Chin, Toshio Tsuji

    9th international Convention on Rehabilitation Engineering & Assistive Technology (i-CREATe2015)   p.2.2_110   2015.11

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  • Change over time of infants' movements based on motion analysis: Comparison with changes in General Movements and the body sway

    Koji Shimatani, Taro Shibanoki, Keisuke Shima, Yuichi Kurita, Akira Otsuka, Maura Casadio, Psiche Giannoni, Paolo Moretti, Pietro Morasso, Toshio Tsuji

    World Confederation for Physical Therapy Congress 2015, Singapore, May 1-4   PO-17-14   2015.5

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  • 未学習クラス推定ニューラルネットの提案と筋電義手制御への応用 Reviewed

    島圭介, 今儀潤一, 早志英朗, 芝軒太郎, 栗田雄一, 辻敏夫

    日本ロボット学会誌   33 ( 4 )   2015

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  • A Neural Network Based Infant Monitoring System to Facilitate Diagnosis of Epileptic Seizures Reviewed

    Yuya Ogura, Hideaki Hayashi, Shota Nakashima, Zu Soh, Taro Shibanoki, Koji Shimatani, Akihito Takeuchi, Makoto Nakamura, Akihisa Okumura, Yuichi Kurita, Toshio Tsuji

    Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’15), Milano, Italy, August 25th-29th   5614-5617   2015

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  • Operation Assistance for the Bio-Remote Environmental Control System Using a Bayesian Network-based Prediction Model Reviewed

    Taro Shibanoki, Go Nakamura, Keisuke Shima, Takaaki Chin, Toshio Tsuji

    Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’15), Milano, Italy, August 25th-29th   1160-1163   2015

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  • 時系列判別成分分析に基づく次元圧縮型リカレント確率ニューラルネット Reviewed

    早志 英朗, 島 圭介, 芝軒 太郎, 栗田 雄一, 辻 敏夫

    計測自動制御学会論文集   50 ( 4 )   2014

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  • A marker-less monitoring system for behavior analysis of infant using video image Reviewed

    Migita Ryo, Shimatani Koji, Shibanoki Taro, Kurita Yuichi, Shima Keisuke, Tsuji Toshio

    Japan Journal of Human Growth and Development Research   2014 ( 65 )   1 - 7   2014

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    This paper proposes a behavior analysis system for quantitative evaluation of infants with attention deficit hyperactivity disorder (ADHD) using video images. The system records infantsʼ movements using video cameras without any markers, and quantitatively evaluates each infantʼs behavior using features extracted from video images based on the behavior model. In the experiments performed, behaviors of infants in nursery school were evaluated using the proposed system. The results showed that the behavior of a high-risk infant significantly different from those of normal infants. These outcomes indicated that the proposed system could discriminate the behavior of normal infants and high-risk infants.

    DOI: 10.5332/hatsuhatsu.2014.65_1

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  • 新生児の自発運動評価を目的としたGeneral Movements診断支援システム Reviewed

    中島 翔太, 右田 涼, 早志 英朗, 芝軒 太郎, 島 圭介, 島谷 康司, 中塚 幹也, 竹内 章人, 中村 信, 栗田 雄一, 辻 敏夫

    計測自動制御学会論文集   50 ( 9 )   2014

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  • 因子分析によるパーキンソン病患者の指タップ運動機能評価と分類 Reviewed

    島圭介, 山口裕希, 芝軒太郎, 辻敏夫, 神鳥明彦, 佐野佑子, 佐古田三郎

    計測自動制御学会論文集   49 ( 10 )   975-981   2013.10

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  • 同時事後確率推定ニューラルネットを用いた双腕動作識別法 Reviewed

    島圭介, 平松侑樹, 芝軒太郎, 辻敏夫

    計測自動制御学会論文集   49 ( 5 )   568-575   2013.5

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  • A Quasi-Optimal Channel Selection Method for Bioelectric Signal Classification Using a Partial KL Information Measure Reviewed

    Taro Shibanoki, Keisuke Shima, Toshio Tsuji, Akira Otsuka, Takaaki Chin

    IEEE Transactions on Biomedical Engineering   60 ( 3 )   853-861   2013.3

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  • A Training System for the MyoBock hand in a Virtual Reality Environment Reviewed

    Go Nakamura, Taro Shibanoki, Keisuke Shima, Yuichi Kurita, Masaki Hasegawa, Akira Otsuka, Yuichiro Honda, Takaaki Chin, Toshio Tsuji

    Proceedings of IEEE Biomedical Circuits and Systems Conference (BioCAS2013)   5394-5397   2013

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  • CPGシナジー仮説:非定常リズム信号を生成可能なCPGシナジーモデルの提案と指タップ運動の表現 Reviewed

    島圭介, 丸元崇弘, 芝軒太郎, 栗田雄一, 辻敏夫, 神鳥明彦, 佐野佑子, 吉栖正生, 佐古田三郎

    計測自動制御学会論文集   49 ( 7 )   688-695   2013

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  • Bioelectric Signal Classification Using a Recurrent Probabilistic Neural Network with Time-series Discriminant Component Analysis Reviewed

    Hideaki Hayashi, Keisuke Shima, Taro Shibanoki, Yuichi Kurita, Toshio Tsuji

    Proceedings of 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'13)   5394-5397   2013

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  • 箔状圧電センサを利用した頸髄損傷患者のためのPC操作インタフェース Reviewed

    島圭介, 杉江研勇, 芝軒太郎, 卜楠, 上野直広, 吉栖正生, 辻敏夫

    計測自動制御学会論文集   48 ( 12 )   854-862   2012.12

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  • A Class Selection Method Based on a Partial Kullback-Leibler Information Measure for Biological Signal Classification Reviewed

    Taro Shibanoki, Keisuke Shima, Takeshi Takaki, Yuichi Kurita, Akira Otsuka, Takaaki Chin, Toshio Tsuji

    2012 IEEE/ICME International Conference on Complex Medical Engineering (CME 2012)   276-279   2012.12

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  • VRを利用した筋電義手操作トレーニングシステムの開発と仮想Box and Block Testの実現 Reviewed

    芝軒太郎, 村上隆治, 島圭介, 辻敏夫, 大塚彰, 陳隆明

    日本ロボット学会誌   30 ( 6 )   621-628   2012.8

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  • 偏KL情報量に基づくクラス選択法の提案とEMG識別のための動作選定問題への応用 Reviewed

    芝軒太郎, 島圭介, 高木健, 栗田雄一, 大塚彰, 陳隆明, 辻敏夫

    計測自動制御学会論文集   48 ( 9 )   580-588   2012

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  • Multi-channel surface EMG classification based on a quasi-optimal selection of motions and channels Reviewed

    Taro Shibanoki, Keisuke Shima, Takeshi Takaki, Yuichi Kurita, Akira Otsuka, Takaaki Chin, Toshio Tsuji

    2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings   276 - 279   2012

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    This paper introduces a motion and channel selection method based on a partial Kullback-Leibler (KL) information measure. In the proposed method, the probability density functions of recorded data are estimated through learning involving a probabilistic neural network based on the KL information theory. Partial KL information is defined to support evaluation of the contribution of each dimension and class for classification. Effective dimensions and classes can then be selected by eliminating ineffective choices one by one based on this information, respectively. In the experiments, effective channels for classification were first selected for each of the six subjects, and the number of channels was reduced by 32.1 ± 25.5%. After channel selection, appropriate motions for classification were chosen, and the average classification rate for the motions selected using the proposed method was found to be 91.7 ± 2.5%. These outcomes indicate that the proposed method can be used to select effective channels and motions for accurate classification. © 2012 IEEE.

    DOI: 10.1109/ICCME.2012.6275609

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  • A Novel Dual-arm Motion Discrimination Method Using Recurrent Probability Neural Networks for Automatic Gesture Recognition Reviewed

    Yuki Hiramatsu, Taro Shibanoki, Keisuke Shima, Toshio Tsuji

    Proceedings of the 2011 IEEE/SICE International Symposium on System Integration (SII 2011)   1346-1351   2011.12

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  • A Class Selection Method Based on a Partial Kullback-Leibler Information Measure for Biological Signal Classification Reviewed

    Taro Shibanoki, Keisuke Shima, Takeshi Takaki, Toshio Tsuji, Akira Otsuka, Takaaki Chin

    Proceedings of the 2010 IEEE/SICE International Symposium on System Integration (SII 2010)   317-322   2010.12

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  • 偏KL情報量に基づく変数選択法と生体電極選定への応用 Reviewed

    芝軒太郎, 島圭介, 辻敏夫, 高木健, 大塚彰, 陳隆明

    計測自動制御学会論文集   45 ( 12 )   724-730   2009.6

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  • A Novel Channel Selection Method Based on Partial KL Information Measure for EMG-based Motion Classification Reviewed

    Taro Shibanoki, Keisuke Shima, Toshio Tsuji, Akira Otsuka, Takaaki Chin

    ICBME2008 - 13th International Conference on Biomedical Engineering (IFMBE Proceedings, Vol. 23)   694-698   2008

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  • Biological Signal Recognition by Fast Statistical Learning Algorithm Reviewed

    Taro Shibanoki, Tadahiro Oyama, Stephen Githinji Karungaru, Satoru Tsuge, Yasue Mitsukura, Minoru Fukumi

    Proceedings of MJISAT' 2007   T2-4-1-T2-4-6   2007.11

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Books

  • Handbook of Research on Biomimetics and Biomedical Robotics, Edited by Maki K. Habib

    Taro Shibanoki, Toshio Tsuji( Role: Joint author)

    IGI Global  2017  ( ISBN:1522529934

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    Responsible for pages:Chapter 15. Discrimination of Dual-arm Motions Using a Joint Posterior Probability Neural Network fo   Language:English

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  • Handbook on Research on Advancement in Robotics and Mechatronics, Edited by Maki K. Habib

    Toshio Tsuji, Taro Shibanoki, Keisuke Shima( Role: Joint author)

    IGI Global  2014  ( ISBN:9781466673878

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    Responsible for pages:Chapter 3. EMG-based control of a multi-joint robot for operating a glovebox, pp. 36-52   Language:English

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MISC

  • Development of Myoelectric Robotic/Prosthetic Hands with Cybernetic Control at the Biological Systems Engineering Laboratory Hiroshima University Invited

    Toshio Tsuji, Taro Shibanoki, Go Nakamura, Akira Furui

    Journal of Robotics and Mechatronics   31 ( 1 )   27 - 34   2019.2

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    This review introduces our developed robotic/prosthetic hands and explains the myoelectric control of the robotic hand with five fingers, which is based on muscle synergy and a motion generation model. To realize a “human-like” robotic hand, it is necessary to fully understand the inherent features of human as well as machine and take a complementary approach with hardware that incorporates advanced engineering technology and software that is compatible with a living body.

    DOI: 10.20965/jrm.2019.p0027

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  • バーチャルリアリティを利用した相互学習型筋電義手トレーニングシステム

    渡橋史典, 芝軒太郎, 栗田雄一, 島谷康司, 長谷川正哉, 大塚彰, 中村豪, 中村豪, 本田雄一郎, 陳隆明, 辻敏夫

    日本機械学会ロボティクス・メカトロニクス講演会講演論文集(CD-ROM)   2014   ROMBUNNO.3P2‐G01   2014.5

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    J-GLOBAL

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  • 3A1-T05 Modularization of an Environmental Control System "Bio-remote" Using OpenRTM(RT Middleware and Open Systems)

    NAKAMURA Go, HONDA Yuichiro, SHIBANOKI Taro, CHIN Takaaki, TSUJI Toshio

    2014   "3A1 - T05(1)"-"3A1-T05(4)"   2014.5

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    Language:Japanese   Publisher:The Japan Society of Mechanical Engineers  

    In this paper, we aim to develop a custom-made environment control system (ECS) in order to support daily living for physically handicapped persons. We modularized the ECS "Bio-remote" developed at Hiroshima University based on OpenRTM. The modularity enhanced flexibility and expandability of Bio-remote, and it made possible to operate by combining multiple input signals. In addition, we performed a trial test with an upper limb amputee in a room which was build to evaluate Bio-remote. We confirmed the operation of the prototype system and the advantage of the modularity that the system function can be easily modified and added.

    CiNii Article

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  • 2B2-4 Development of a Five-Finger EMG-Prosthetic Hand with Grasp-Force Magnification Mechanism

    SHIMA Keisuke, TAKAKI Takeshi, SHIBANOKI Taro, TSUJI Toshio, OMATA Toru, OTSUKA Akira, CHIN Takaaki

    FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies   2011 ( 21 )   273 - 276   2011.9

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    This paper proposes a five-fingered EMG-prosthetic hand, which enables a quick motion and a secure grasp. In order to realize the natural feeling of control similar to that of human movements, the control system includes the impedance model of human forearms, and utilizes the muscle contraction level extracted from the user's EMG signals. To verify the effectiveness of the developed prosthetic hand, the control experiments of quick motion and secure grasp using EMG signals performed with a subject.

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  • 5指駆動型筋電義手と筋シナジーモデルに基づく制御法

    辻敏夫, 芝軒太郎, 島圭介, 高木健, 大塚彰, 陳隆明

    日本義肢装具学会誌   26 ( 2 )   91-96   2010.4

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Presentations

  • 1P2-K05 Training System for the Five-finger EMG-prosthetic Hand Using Virtual Reality

    ETO Shintaro, TSUJI Toshio, ORIHASHI Fuminori, HAYASHI Hideaki, NAKAMURA Go, SHIBANOKI Taro, TAKAKI Takeshi, KURITA Yuichi, HONDA Yuichiro, CHIN Takaaki

    The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)  2015  The Japan Society of Mechanical Engineers

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    This paper proposes a training system for controlling the five-finger EMG-prosthetic hand that enables not only fast finger motions but also a strong grasping force. The proposed system is developed based on the control method equivalent to the five-finger prosthetic hand, and conducts three types of training: muscle contraction, muscle cooperation, and grip force training. In the contraction training and the cooperation training, the control ability of muscle force and the reproducibility of EMG patterns can be trained, respectively. Appropriate gripping force according to the hardness of an object can also be trained via the grip force training using a virtual prosthetic hand. The validity of the proposed system is demonstrated in the five-day experiments conducted for three subjects.

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  • 3A1-T05 Modularization of an Environmental Control System "Bio-remote" Using OpenRTM(RT Middleware and Open Systems)

    NAKAMURA Go, HONDA Yuichiro, SHIBANOKI Taro, CHIN Takaaki, TSUJI Toshio

    2014.5.24  The Japan Society of Mechanical Engineers

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    Event date: 2014.5.24

    Language:Japanese  

    In this paper, we aim to develop a custom-made environment control system (ECS) in order to support daily living for physically handicapped persons. We modularized the ECS "Bio-remote" developed at Hiroshima University based on OpenRTM. The modularity enhanced flexibility and expandability of Bio-remote, and it made possible to operate by combining multiple input signals. In addition, we performed a trial test with an upper limb amputee in a room which was build to evaluate Bio-remote. We confirmed the operation of the prototype system and the advantage of the modularity that the system function can be easily modified and added.

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  • 2B2-4 Development of a Five-Finger EMG-Prosthetic Hand with Grasp-Force Magnification Mechanism

    SHIMA Keisuke, TAKAKI Takeshi, SHIBANOKI Taro, TSUJI Toshio, OMATA Toru, OTSUKA Akira, CHIN Takaaki

    FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies  2011.9.1  The Japan Society of Mechanical Engineers

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    Event date: 2011.9.1

    Language:Japanese  

    This paper proposes a five-fingered EMG-prosthetic hand, which enables a quick motion and a secure grasp. In order to realize the natural feeling of control similar to that of human movements, the control system includes the impedance model of human forearms, and utilizes the muscle contraction level extracted from the user's EMG signals. To verify the effectiveness of the developed prosthetic hand, the control experiments of quick motion and secure grasp using EMG signals performed with a subject.

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  • 動作指示が可能な筋協調制御訓練システム

    鳥井保秀, 芝軒太郎, 中村豪, 陳隆明, 辻敏夫

    第29回ライフサポート学会フロンティア講演会  2020.3.12 

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  • 作業モデルを内包した3Dプリンタブル筋電義手

    神 弘輔, 芝軒 太郎

    第28回ライフサポート学会フロンティア講演会  2019.3.15 

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  • 誤認識を利用した代用発声システム

    菅野 亮太, 芝軒 太郎, 中村 豪, 陳 隆明, 辻 敏夫

    第17回公益社団法人計測自動制御学会システムインテグレーション部門講演会(SI2016)  2016 

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  • クラス偏KL情報量を利用した相互学習型筋電義手訓練システム

    富澤 太, 芝軒 太郎, 陳 隆明, 辻 敏夫

    日本機械学会ロボティクス・メカトロニクス講演会2016  2016 

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  • 耳介への刺激が身体動揺に与える影響

    渡邊 聖和, 芝軒 太郎, 島谷 康司

    LIFE 2016(第32回ライフサポート学会大会,第16回日本生活支援工学会大会,日本機械学会福祉工学シンポジウム2016)  2016 

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  • 新生児General Movements評価支援システムの精度検証

    木下 直樹, 川嶋 克明, 尾倉 侑也, 早志 英朗, 曽 智, 芝軒 太郎, 森 裕紀, 島谷 康司, 栗田 雄一, 辻 敏夫

    日本発達神経科学学会第5回学術集会  2016 

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  • バーチャルリアリティを利用した5指駆動型筋電義手のためのトレーニングシステム

    江藤慎太郎, 渡橋史典, 早志英朗, 中村豪, 芝軒太郎, 高木健, 栗田雄一, 本田雄一郎, 陳隆明, 辻敏夫

    日本機械学会ロボティクス・メカトロニクス講演会2015  2015 

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  • Development of a Virtual Training System for Myoelectric Prostheses

    Go Nakamura, Taro Shibanoki, Keisuke Shima, Yuichi Kurita, Yuichiro Honda, Takaaki Chin, Toshio Tsuji

    Asian Prosthetic and Orthotic Scientific Meeting 2014 in conjunction with The Second Meeting of the International Society for Restorative Neurology (APOSM2014 & ISRN)  2014.11.30 

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  • マーカーレス運動解析システムに基づく新生児運動の経時的変化

    芝軒 太郎, 島谷 康司, 島 圭介, 辻 敏夫

    日本発達神経科学会第3回大会  2014 

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  • バーチャルリアリティを利用した相互学習型筋電義手トレーニングシステム

    渡橋史典, 芝軒太郎, 栗田雄一, 島谷康司, 長谷川正哉, 大塚彰, 中村豪, 本田雄一郎, 陳隆明, 辻敏夫

    日本機械学会ロボティクス・メカトロニクス講演会2014  2014 

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  • OpenRTMを利用した環境制御装置「バイオリモート」のモジュール化

    中村豪, 本田雄一郎, 芝軒太郎, 陳隆明, 辻敏夫

    日本機械学会ロボティクス・メカトロニクス講演会2014  2014 

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  • てんかん発作診断支援のための乳幼児モニタリングシステム

    尾倉 侑也, 中島 翔太, 右田 涼, 早志 英朗, 曽 智, 芝軒 太郎, 島谷 康司, 竹内 章人, 中村 信, 奥村 彰久, 栗田 雄一, 辻 敏夫

    平成26年度日本人間工学会中国・四国支部,関西支部合同大会  2014 

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  • 新生児の自発運動評価を目的としたGeneral Movements診断支援システム

    中島 翔太, 右田 涼, 早志 英朗, 曽 智, 芝軒 太郎, 島 圭介, 島谷 康司, 中塚 幹也, 竹内 章人, 中村 信, 栗田 雄一, 辻 敏夫

    日本発達神経科学会第3回大会  2014 

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  • 動画像解析に基づく乳幼児行動マーカーレスモニタリングシステム

    右田 涼, 島谷 康司, 曽 智, 芝軒 太郎, 栗田 雄一, 島 圭介, 辻 敏夫

    日本発達神経科学会第3回大会  2014 

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  • General Movements評価のためのマーカレス新生児運動モニタリングシステム

    第46回日本人間工学会中国・四国支部大会  2013 

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  • 筋音図を利用した多自由度義手の制御

    第3回全国電動義手研究会  2012 

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  • 未学習クラス推定ニューラルネットによる筋電義手制御

    第45回日本人間工学会中国・四国支部大会  2012 

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  • 音声信号を利用した環境制御装置Bio-Remoteの操作方式

    第45回日本人間工学会中国・四国支部大会  2012 

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  • 動画像解析に基づく乳幼児行動マーカーレスモニタリングシステム

    第13回計測自動制御学会システムインテグレーション部門講演会  2012 

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  • 把持力増大機構を有する5 指駆動型筋電義手

    第21回インテリジェント・システム・シンポジウム  2011 

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  • 非定常リズム信号を生成可能なCPGシナジーモデルの提案と指タップ運動機能評価への応用

    第12回計測自動制御学会システムインテグレーション部門講演会  2011 

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  • 筋電義手操作のためのバーチャルトレーニングシステムの提案と仮想Box and Block Testの実現

    第20回計測自動制御学会中国支部学術講演会  2011 

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  • 次元圧縮型確率ニューラルネットを用いたブレイン・マシン・インタフェース

    日本人間工学会中国・四国支部九州・沖縄支部合同開催支部大会  2011 

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  • Otto Bock筋電義手操作を目的としたバーチャルトレーニングシステム

    日本人間工学会中国・四国支部九州・沖縄支部合同開催支部大会  2011 

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  • 判別成分分析に基づく新しい次元圧縮型リカレント確率ニューラルネット

    第12回計測自動制御学会システムインテグレーション部門講演会  2011 

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  • 偏KL情報量に基づく動作選定法~ヒトとシステムが相互に学習可能な訓練システムの実現を目指して~

    第2回全国電動義手研究会  2011 

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  • 筋電義手操作を目的としたバーチャルトレーニングシステムの提案

    第2回全国電動義手研究会  2011 

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  • 加速度信号を用いたバイオミュージックシステム

    第19回計測自動制御学会中国支部学術講演会  2010 

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  • 頚椎損傷患者のための箔状圧電センサを利用したマスク型インタフェース

    日本人間工学会第43回中国・四国支部大会  2010 

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  • 5指駆動型筋電義手と筋シナジーモデルに基づく新しい制御法

    第25回日本義肢装具学会学術大会  2009 

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  • 把持力増大機構を有する5指駆動型義手の筋電制御

    第3回義手を語る会  2009 

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  • 筋電義手操作トレーニングを目的としたバーチャルハンド制御システム

    電気・情報関連学会中国支部第60回連合大会  2009 

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  • 偏KL量に基づく電極選定法

    第3回義手を語る会  2009 

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  • 加速度センサを用いた新しい双腕動作識別法とロボット制御への応用

    第42回日本人間工学会中国・四国支部大会  2009 

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Awards

  • SI2016優秀講演賞

    2016   計測自動制御学会  

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  • 計測自動制御学会論文賞

    2014  

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  • 日本人間工学会中国四国支部優秀論文賞

    2012   日本人間工学会中国・四国支部  

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  • 第21回インテリジェント・システム・シンポジウムプレゼンテーション賞

    2011   日本機械学会  

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Research Projects

  • 痛みを感じる義手:振動刺激に基づく違和感フィードバックと人間らしい制御の試み

    Grant number:20K20212  2020.04 - 2023.03

    日本学術振興会  科学研究費助成事業 若手研究  若手研究

    芝軒 太郎

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    Grant amount:\4160000 ( Direct expense: \3200000 、 Indirect expense:\960000 )

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  • 双腕協調タスクモデルに基づく5指駆動型筋電電動義手の提案と義手処方支援

    Grant number:17K12723  2017.04 - 2021.03

    日本学術振興会  科学研究費助成事業 若手研究(B)  若手研究(B)

    芝軒 太郎

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    Grant amount:\4160000 ( Direct expense: \3200000 、 Indirect expense:\960000 )

    本年度は,双腕で行う作業のモデル化を進め,各腕の姿勢情報から推定した作業状態に応じた制御を行うことで,安定した動作が可能な新たな3Dプリンタブル筋電義手を開発した [The 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2020)].実験では,提案義手を用いて実際に義肢と健常肢とを協調させた作業を行い,蓋を開けるなど,両腕を使った作業を安定して実行できることを示した.また,日常生活において筋電義手をより安定して制御可能とするために,双腕作業を考慮した新たなトレーニングシステムおよびトレーニングにおける動作の指示法について検討を行った.提案システムではVR環境下に構築したVirtual Hand(VH)を切断肢では筋電位,健常肢では各指の姿勢情報に基づいて制御可能である.提案システムは訓練の難易度を調整可能であり,訓練者の能力に応じたステージの提示や指示を行うことで訓練者の能力を効率的に向上できる [LifeTech 2020,第29回ライフサポート学会フロンティア講演会].
    さらに,使用者の生体信号制御能力を評価して訓練に用いる試みはさまざまな生体信号インタフェースに応用できることを発見し,動作イメージ制御型ブレイン・コンピューター・インタフェースおよび音声で操作可能な環境制御装置に展開した.実験では,短時間の訓練で動作イメージを精度良く制御できること [LifeTech2020],また,使用者の発話能力に合わせた追加学習/訓練により,不明瞭な発話であっても安定した識別が実現できることを明らかにした [SICE Annual Conference 2019 (SICE 2019)].

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  • Development of a control method for a myoelectric prosthetic hand with independently driven five fingers based on the muscle synergy model

    Grant number:26462242  2014.04 - 2017.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)  Grant-in-Aid for Scientific Research (C)

    Chin Takaaki

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    Grant amount:\4940000 ( Direct expense: \3800000 、 Indirect expense:\1140000 )

    This study proposed a control method for a myoelectric prosthetic hand capable of performing multiple motions and a training system for myoelectric prosthetic hand control using virtual reality (VR) technology. A myoelectric prosthetic hand was also developed by using a 3D printer and a microcomputer. The developed myoelectric prosthetic hand can discriminate multiple motions by using a discrimination method based on the muscle synergy model. The proposed training system allows the amputees to practice grasping/releasing objects in a VR environment.

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  • Speech controlled environmental control system: Bio-Remote for the physically challenged based on candidate word discriminations

    Grant number:26330226  2014.04 - 2017.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)  Grant-in-Aid for Scientific Research (C)

    SHIBANOKI Taro

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    Grant amount:\4680000 ( Direct expense: \3600000 、 Indirect expense:\1080000 )

    This study proposed a speech controlled environmental control system (ECS): Bio-Remote (BR) based on candidate word discriminations and realized operation assistance using a Bayesian network-based prediction model. In order to maintain an independent life for the physically challenged, this study also proposed robotic manipulator control based on the BR, and obstacle avoidance method for mobile robots.

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  • 共創型人間‐機械インタフェースの提案と筋電義手処方支援システムの開発

    Grant number:11J00522  2011 - 2012

    日本学術振興会  科学研究費助成事業 特別研究員奨励費  特別研究員奨励費

    芝軒 太郎

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    Grant amount:\1300000 ( Direct expense: \1300000 )

    本年度は,筋電義手制御のための電極・動作選定法および筋電義手をはじめとするさまざまな機器の制御法について検討を行った.まず,偏KL情報量に基づく筋電位計測のための適切な電極貼付位置選定法を提案した.偏KL情報量はあらかじめ貼付した電極のうち,ある電極を除去した際の情報量の偏りを表しており,各電極が動作の識別に必要か否かを判別できる.偏KL情報量に従って識別に不要な電極を逐次削除することで,適切な電極を選定可能である.提案法では,筋電位の学習・識別に確率ニューラルネットを用いており,KL情報量最小化に基づく学習則を導入することで,ニューラルネットの学習と各電極が識別に与える影響度を同時に評価可能である.実験では。上肢切断者を含む全9名を対象に筋電位信号識別実験を行い,あらかじめ貼付した多数の電極から識別に必要な少数の電極を選定できること,選定電極のみを用いて精度良い動作識別が可能であることを示した[IEEE Transactions on Biomedical Engineering].次に,偏KL情報量を識別対象動作の選定に応用し,被験者が随意的に再現可能な動作(識別可能動作)を選定する方法を提案した.また,電極選定法と提案する動作選定法を組合せることで適切な電極と動作を同時に選定可能とした.実験では,あらかじめ被験者に手首・指に関連する動作を多数実施させ,提案法を用いて識別可能動作のみを選定できることを示すとともに,電極と動作の同時選定を行い,適切な電極と動作を偏KL情報量という統一的な枠組みによって一挙に獲得できることを示した.[計測自動制御学会論文集,IEEE/CME International Conference on ComPlex Medical Engineering (CME2012)].
    また,予期しない未学習動作を識別可能なニューラルネットを提案し,誤動作を防止した筋電義手制御を実現した.さらに,音声信号や圧電信号などの生体信号を制御入力とした新たなPC・家電機器制御インタフェースを開発した[計測自動制御学会論文集,日本人間工学会中国四国支部大会].
    一方,多数の乳幼児の行動をマーカーレスに計測し,画像処理によって行動を抽出・モデル化することで,健常児と車門家が指摘するハイリスク児との行動の違いを明らかにした[SI2012].

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  • Seminar in Mechatronic Systems (2021academic year) Year-round  - その他

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