A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients

Jongseung Lee, Nobutaka Mukae, Jumpei Arata, Hiroyuki Iwata, Keiji Iramina, Koji Iihara, Makoto Hashizume

研究成果: 著書/レポートタイプへの貢献会議での発言

2 引用 (Scopus)

抄録

There is a demand for a new neurorehabilitation modality with a brain-computer interface for stroke patients with insufficient or no remaining hand motor function. We previously developed a robotic hand rehabilitation system triggered by multichannel near-infrared spectroscopy (NIRS) to address this demand. In a preliminary prototype system, a robotic hand orthosis, providing one degree-of-freedom motion for a hand's closing and opening, is triggered by a wireless command from a NIRS system, capturing a subject's motor cortex activation. To examine the feasibility of the prototype, we conducted a preliminary test involving six neurologically intact participants. The test comprised a series of evaluations for two aspects of neurorehabilitation training in a real-time manner: classification accuracy and execution time. The effects of classification-related factors, namely the algorithm, signal type, and number of NIRS channels, were investigated. In the comparison of algorithms, linear discrimination analysis performed better than the support vector machine in terms of both accuracy and training time. The oxyhemoglobin versus deoxyhemoglobin comparison revealed that the two concentrations almost equally contribute to the hand motion estimation. The relationship between the number of NIRS channels and accuracy indicated that a certain number of channels are needed and suggested a need for a method of selecting informative channels. The computation time of 5.84 ms was acceptable for our purpose. Overall, the preliminary prototype showed sufficient feasibility for further development and clinical testing with stroke patients.

元の言語英語
ホスト出版物のタイトル2017 International Conference on Rehabilitation Robotics, ICORR 2017
編集者Arash Ajoudani, Panagiotis Artemiadis, Philipp Beckerle, Giorgio Grioli, Olivier Lambercy, Katja Mombaur, Domen Novak, Georg Rauter, Carlos Rodriguez Guerrero, Gionata Salvietti, Farshid Amirabdollahian, Sivakumar Balasubramanian, Claudio Castellini, Giovanni Di Pino, Zhao Guo, Charmayne Hughes, Fumiya Iida, Tommaso Lenzi, Emanuele Ruffaldi, Fabrizio Sergi, Gim Song Soh, Marco Caimmi, Leonardo Cappello, Raffaella Carloni, Tom Carlson, Maura Casadio, Martina Coscia, Dalia De Santis, Arturo Forner-Cordero, Matthew Howard, Davide Piovesan, Adriano Siqueira, Frank Sup, Masia Lorenzo, Manuel Giuseppe Catalano, Hyunglae Lee, Carlo Menon, Stanisa Raspopovic, Mo Rastgaar, Renaud Ronsse, Edwin van Asseldonk, Bram Vanderborght, Madhusudhan Venkadesan, Matteo Bianchi, David Braun, Sasha Blue Godfrey, Fulvio Mastrogiovanni, Andrew McDaid, Stefano Rossi, Jacopo Zenzeri, Domenico Formica, Nikolaos Karavas, Laura Marchal-Crespo, Kyle B. Reed, Nevio Luigi Tagliamonte, Etienne Burdet, Angelo Basteris, Domenico Campolo, Ashish Deshpande, Venketesh Dubey, Asif Hussain, Vittorio Sanguineti, Ramazan Unal, Glauco Augusto de Paula Caurin, Yasuharu Koike, Stefano Mazzoleni, Hyung-Soon Park, C. David Remy, Ludovic Saint-Bauzel, Nikos Tsagarakis, Jan Veneman, Wenlong Zhang
出版者IEEE Computer Society
ページ158-163
ページ数6
ISBN(電子版)9781538622964
DOI
出版物ステータス出版済み - 8 11 2017
イベント2017 International Conference on Rehabilitation Robotics, ICORR 2017 - London, 英国
継続期間: 7 17 20177 20 2017

出版物シリーズ

名前IEEE International Conference on Rehabilitation Robotics
ISSN(印刷物)1945-7898
ISSN(電子版)1945-7901

その他

その他2017 International Conference on Rehabilitation Robotics, ICORR 2017
英国
London
期間7/17/177/20/17

Fingerprint

Near infrared spectroscopy
Near-Infrared Spectroscopy
Robotics
End effectors
Patient rehabilitation
Hand
Brain computer interface
Stroke
Brain-Computer Interfaces
Motion estimation
Orthotic Devices
Oxyhemoglobins
Support vector machines
Motor Cortex
Chemical activation
Rehabilitation
Stroke Rehabilitation
Testing

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Rehabilitation
  • Medicine(all)

これを引用

Lee, J., Mukae, N., Arata, J., Iwata, H., Iramina, K., Iihara, K., & Hashizume, M. (2017). A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients. : A. Ajoudani, P. Artemiadis, P. Beckerle, G. Grioli, O. Lambercy, K. Mombaur, D. Novak, G. Rauter, C. Rodriguez Guerrero, G. Salvietti, F. Amirabdollahian, S. Balasubramanian, C. Castellini, G. Di Pino, Z. Guo, C. Hughes, F. Iida, T. Lenzi, E. Ruffaldi, F. Sergi, G. S. Soh, M. Caimmi, L. Cappello, R. Carloni, T. Carlson, M. Casadio, M. Coscia, D. De Santis, A. Forner-Cordero, M. Howard, D. Piovesan, A. Siqueira, F. Sup, M. Lorenzo, M. G. Catalano, H. Lee, C. Menon, S. Raspopovic, M. Rastgaar, R. Ronsse, E. van Asseldonk, B. Vanderborght, M. Venkadesan, M. Bianchi, D. Braun, S. B. Godfrey, F. Mastrogiovanni, A. McDaid, S. Rossi, J. Zenzeri, D. Formica, N. Karavas, L. Marchal-Crespo, K. B. Reed, N. L. Tagliamonte, E. Burdet, A. Basteris, D. Campolo, A. Deshpande, V. Dubey, A. Hussain, V. Sanguineti, R. Unal, G. A. D. P. Caurin, Y. Koike, S. Mazzoleni, H-S. Park, C. D. Remy, L. Saint-Bauzel, N. Tsagarakis, J. Veneman, ... W. Zhang (版), 2017 International Conference on Rehabilitation Robotics, ICORR 2017 (pp. 158-163). [8009239] (IEEE International Conference on Rehabilitation Robotics). IEEE Computer Society. https://doi.org/10.1109/ICORR.2017.8009239

A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients. / Lee, Jongseung; Mukae, Nobutaka; Arata, Jumpei; Iwata, Hiroyuki; Iramina, Keiji; Iihara, Koji; Hashizume, Makoto.

2017 International Conference on Rehabilitation Robotics, ICORR 2017. 版 / Arash Ajoudani; Panagiotis Artemiadis; Philipp Beckerle; Giorgio Grioli; Olivier Lambercy; Katja Mombaur; Domen Novak; Georg Rauter; Carlos Rodriguez Guerrero; Gionata Salvietti; Farshid Amirabdollahian; Sivakumar Balasubramanian; Claudio Castellini; Giovanni Di Pino; Zhao Guo; Charmayne Hughes; Fumiya Iida; Tommaso Lenzi; Emanuele Ruffaldi; Fabrizio Sergi; Gim Song Soh; Marco Caimmi; Leonardo Cappello; Raffaella Carloni; Tom Carlson; Maura Casadio; Martina Coscia; Dalia De Santis; Arturo Forner-Cordero; Matthew Howard; Davide Piovesan; Adriano Siqueira; Frank Sup; Masia Lorenzo; Manuel Giuseppe Catalano; Hyunglae Lee; Carlo Menon; Stanisa Raspopovic; Mo Rastgaar; Renaud Ronsse; Edwin van Asseldonk; Bram Vanderborght; Madhusudhan Venkadesan; Matteo Bianchi; David Braun; Sasha Blue Godfrey; Fulvio Mastrogiovanni; Andrew McDaid; Stefano Rossi; Jacopo Zenzeri; Domenico Formica; Nikolaos Karavas; Laura Marchal-Crespo; Kyle B. Reed; Nevio Luigi Tagliamonte; Etienne Burdet; Angelo Basteris; Domenico Campolo; Ashish Deshpande; Venketesh Dubey; Asif Hussain; Vittorio Sanguineti; Ramazan Unal; Glauco Augusto de Paula Caurin; Yasuharu Koike; Stefano Mazzoleni; Hyung-Soon Park; C. David Remy; Ludovic Saint-Bauzel; Nikos Tsagarakis; Jan Veneman; Wenlong Zhang. IEEE Computer Society, 2017. p. 158-163 8009239 (IEEE International Conference on Rehabilitation Robotics).

研究成果: 著書/レポートタイプへの貢献会議での発言

Lee, J, Mukae, N, Arata, J, Iwata, H, Iramina, K, Iihara, K & Hashizume, M 2017, A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients. : A Ajoudani, P Artemiadis, P Beckerle, G Grioli, O Lambercy, K Mombaur, D Novak, G Rauter, C Rodriguez Guerrero, G Salvietti, F Amirabdollahian, S Balasubramanian, C Castellini, G Di Pino, Z Guo, C Hughes, F Iida, T Lenzi, E Ruffaldi, F Sergi, GS Soh, M Caimmi, L Cappello, R Carloni, T Carlson, M Casadio, M Coscia, D De Santis, A Forner-Cordero, M Howard, D Piovesan, A Siqueira, F Sup, M Lorenzo, MG Catalano, H Lee, C Menon, S Raspopovic, M Rastgaar, R Ronsse, E van Asseldonk, B Vanderborght, M Venkadesan, M Bianchi, D Braun, SB Godfrey, F Mastrogiovanni, A McDaid, S Rossi, J Zenzeri, D Formica, N Karavas, L Marchal-Crespo, KB Reed, NL Tagliamonte, E Burdet, A Basteris, D Campolo, A Deshpande, V Dubey, A Hussain, V Sanguineti, R Unal, GADP Caurin, Y Koike, S Mazzoleni, H-S Park, CD Remy, L Saint-Bauzel, N Tsagarakis, J Veneman & W Zhang (版), 2017 International Conference on Rehabilitation Robotics, ICORR 2017., 8009239, IEEE International Conference on Rehabilitation Robotics, IEEE Computer Society, pp. 158-163, 2017 International Conference on Rehabilitation Robotics, ICORR 2017, London, 英国, 7/17/17. https://doi.org/10.1109/ICORR.2017.8009239
Lee J, Mukae N, Arata J, Iwata H, Iramina K, Iihara K その他. A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients. : Ajoudani A, Artemiadis P, Beckerle P, Grioli G, Lambercy O, Mombaur K, Novak D, Rauter G, Rodriguez Guerrero C, Salvietti G, Amirabdollahian F, Balasubramanian S, Castellini C, Di Pino G, Guo Z, Hughes C, Iida F, Lenzi T, Ruffaldi E, Sergi F, Soh GS, Caimmi M, Cappello L, Carloni R, Carlson T, Casadio M, Coscia M, De Santis D, Forner-Cordero A, Howard M, Piovesan D, Siqueira A, Sup F, Lorenzo M, Catalano MG, Lee H, Menon C, Raspopovic S, Rastgaar M, Ronsse R, van Asseldonk E, Vanderborght B, Venkadesan M, Bianchi M, Braun D, Godfrey SB, Mastrogiovanni F, McDaid A, Rossi S, Zenzeri J, Formica D, Karavas N, Marchal-Crespo L, Reed KB, Tagliamonte NL, Burdet E, Basteris A, Campolo D, Deshpande A, Dubey V, Hussain A, Sanguineti V, Unal R, Caurin GADP, Koike Y, Mazzoleni S, Park H-S, Remy CD, Saint-Bauzel L, Tsagarakis N, Veneman J, Zhang W, 編集者, 2017 International Conference on Rehabilitation Robotics, ICORR 2017. IEEE Computer Society. 2017. p. 158-163. 8009239. (IEEE International Conference on Rehabilitation Robotics). https://doi.org/10.1109/ICORR.2017.8009239
Lee, Jongseung ; Mukae, Nobutaka ; Arata, Jumpei ; Iwata, Hiroyuki ; Iramina, Keiji ; Iihara, Koji ; Hashizume, Makoto. / A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients. 2017 International Conference on Rehabilitation Robotics, ICORR 2017. 編集者 / Arash Ajoudani ; Panagiotis Artemiadis ; Philipp Beckerle ; Giorgio Grioli ; Olivier Lambercy ; Katja Mombaur ; Domen Novak ; Georg Rauter ; Carlos Rodriguez Guerrero ; Gionata Salvietti ; Farshid Amirabdollahian ; Sivakumar Balasubramanian ; Claudio Castellini ; Giovanni Di Pino ; Zhao Guo ; Charmayne Hughes ; Fumiya Iida ; Tommaso Lenzi ; Emanuele Ruffaldi ; Fabrizio Sergi ; Gim Song Soh ; Marco Caimmi ; Leonardo Cappello ; Raffaella Carloni ; Tom Carlson ; Maura Casadio ; Martina Coscia ; Dalia De Santis ; Arturo Forner-Cordero ; Matthew Howard ; Davide Piovesan ; Adriano Siqueira ; Frank Sup ; Masia Lorenzo ; Manuel Giuseppe Catalano ; Hyunglae Lee ; Carlo Menon ; Stanisa Raspopovic ; Mo Rastgaar ; Renaud Ronsse ; Edwin van Asseldonk ; Bram Vanderborght ; Madhusudhan Venkadesan ; Matteo Bianchi ; David Braun ; Sasha Blue Godfrey ; Fulvio Mastrogiovanni ; Andrew McDaid ; Stefano Rossi ; Jacopo Zenzeri ; Domenico Formica ; Nikolaos Karavas ; Laura Marchal-Crespo ; Kyle B. Reed ; Nevio Luigi Tagliamonte ; Etienne Burdet ; Angelo Basteris ; Domenico Campolo ; Ashish Deshpande ; Venketesh Dubey ; Asif Hussain ; Vittorio Sanguineti ; Ramazan Unal ; Glauco Augusto de Paula Caurin ; Yasuharu Koike ; Stefano Mazzoleni ; Hyung-Soon Park ; C. David Remy ; Ludovic Saint-Bauzel ; Nikos Tsagarakis ; Jan Veneman ; Wenlong Zhang. IEEE Computer Society, 2017. pp. 158-163 (IEEE International Conference on Rehabilitation Robotics).
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title = "A multichannel-near-infrared-spectroscopy-triggered robotic hand rehabilitation system for stroke patients",
abstract = "There is a demand for a new neurorehabilitation modality with a brain-computer interface for stroke patients with insufficient or no remaining hand motor function. We previously developed a robotic hand rehabilitation system triggered by multichannel near-infrared spectroscopy (NIRS) to address this demand. In a preliminary prototype system, a robotic hand orthosis, providing one degree-of-freedom motion for a hand's closing and opening, is triggered by a wireless command from a NIRS system, capturing a subject's motor cortex activation. To examine the feasibility of the prototype, we conducted a preliminary test involving six neurologically intact participants. The test comprised a series of evaluations for two aspects of neurorehabilitation training in a real-time manner: classification accuracy and execution time. The effects of classification-related factors, namely the algorithm, signal type, and number of NIRS channels, were investigated. In the comparison of algorithms, linear discrimination analysis performed better than the support vector machine in terms of both accuracy and training time. The oxyhemoglobin versus deoxyhemoglobin comparison revealed that the two concentrations almost equally contribute to the hand motion estimation. The relationship between the number of NIRS channels and accuracy indicated that a certain number of channels are needed and suggested a need for a method of selecting informative channels. The computation time of 5.84 ms was acceptable for our purpose. Overall, the preliminary prototype showed sufficient feasibility for further development and clinical testing with stroke patients.",
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AU - Lee, Jongseung

AU - Mukae, Nobutaka

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AU - Iramina, Keiji

AU - Iihara, Koji

AU - Hashizume, Makoto

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N2 - There is a demand for a new neurorehabilitation modality with a brain-computer interface for stroke patients with insufficient or no remaining hand motor function. We previously developed a robotic hand rehabilitation system triggered by multichannel near-infrared spectroscopy (NIRS) to address this demand. In a preliminary prototype system, a robotic hand orthosis, providing one degree-of-freedom motion for a hand's closing and opening, is triggered by a wireless command from a NIRS system, capturing a subject's motor cortex activation. To examine the feasibility of the prototype, we conducted a preliminary test involving six neurologically intact participants. The test comprised a series of evaluations for two aspects of neurorehabilitation training in a real-time manner: classification accuracy and execution time. The effects of classification-related factors, namely the algorithm, signal type, and number of NIRS channels, were investigated. In the comparison of algorithms, linear discrimination analysis performed better than the support vector machine in terms of both accuracy and training time. The oxyhemoglobin versus deoxyhemoglobin comparison revealed that the two concentrations almost equally contribute to the hand motion estimation. The relationship between the number of NIRS channels and accuracy indicated that a certain number of channels are needed and suggested a need for a method of selecting informative channels. The computation time of 5.84 ms was acceptable for our purpose. Overall, the preliminary prototype showed sufficient feasibility for further development and clinical testing with stroke patients.

AB - There is a demand for a new neurorehabilitation modality with a brain-computer interface for stroke patients with insufficient or no remaining hand motor function. We previously developed a robotic hand rehabilitation system triggered by multichannel near-infrared spectroscopy (NIRS) to address this demand. In a preliminary prototype system, a robotic hand orthosis, providing one degree-of-freedom motion for a hand's closing and opening, is triggered by a wireless command from a NIRS system, capturing a subject's motor cortex activation. To examine the feasibility of the prototype, we conducted a preliminary test involving six neurologically intact participants. The test comprised a series of evaluations for two aspects of neurorehabilitation training in a real-time manner: classification accuracy and execution time. The effects of classification-related factors, namely the algorithm, signal type, and number of NIRS channels, were investigated. In the comparison of algorithms, linear discrimination analysis performed better than the support vector machine in terms of both accuracy and training time. The oxyhemoglobin versus deoxyhemoglobin comparison revealed that the two concentrations almost equally contribute to the hand motion estimation. The relationship between the number of NIRS channels and accuracy indicated that a certain number of channels are needed and suggested a need for a method of selecting informative channels. The computation time of 5.84 ms was acceptable for our purpose. Overall, the preliminary prototype showed sufficient feasibility for further development and clinical testing with stroke patients.

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A2 - Di Pino, Giovanni

A2 - Guo, Zhao

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A2 - Iida, Fumiya

A2 - Lenzi, Tommaso

A2 - Ruffaldi, Emanuele

A2 - Sergi, Fabrizio

A2 - Soh, Gim Song

A2 - Caimmi, Marco

A2 - Cappello, Leonardo

A2 - Carloni, Raffaella

A2 - Carlson, Tom

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A2 - Coscia, Martina

A2 - De Santis, Dalia

A2 - Forner-Cordero, Arturo

A2 - Howard, Matthew

A2 - Piovesan, Davide

A2 - Siqueira, Adriano

A2 - Sup, Frank

A2 - Lorenzo, Masia

A2 - Catalano, Manuel Giuseppe

A2 - Lee, Hyunglae

A2 - Menon, Carlo

A2 - Raspopovic, Stanisa

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A2 - Ronsse, Renaud

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A2 - Bianchi, Matteo

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A2 - Karavas, Nikolaos

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A2 - Tagliamonte, Nevio Luigi

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A2 - Basteris, Angelo

A2 - Campolo, Domenico

A2 - Deshpande, Ashish

A2 - Dubey, Venketesh

A2 - Hussain, Asif

A2 - Sanguineti, Vittorio

A2 - Unal, Ramazan

A2 - Caurin, Glauco Augusto de Paula

A2 - Koike, Yasuharu

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