Event Abstract

Brain Computer Interface human platform to control a 4-limb exoskeleton based on the ECoG-recording implant WIMAGINE®: preliminary results

  • 1 CEA/LETI, MINATEC Campus, France

The goal of CLINATEC® Brain Computer Interface Project is to improve tetraplegic subjects’ quality of life by allowing them to interact with their environment through the control of effectors with multiple degrees of freedom after training. Thanks to a long-term wireless 64-channel ECoG recording implant WIMAGINE® (Wireless Implantable Multi-channel Acquisition system for Generic Interface with NEurons) [1] and an innovative signal processing, the subject should be able to control a 4-limb exoskeleton EMY (Enhancing MobilitY) [2]. The ECoG signals from the subject’s brain will be recorded and wirelessly transmitted to a base station by the WIMAGINE® implant. This implant is composed of an array of 64 biocompatible electrodes, a hermetic titanium case which houses electronic boards, biocompatible antennas for wireless transmission of the data, and a remote power supply. The WIMAGINE implant complies with implantable medical device standards. Innovative ECoG signal decoding algorithms will allow self-paced control of the exoskeleton by decoding the subject’s brain activity [3] [4]. The neuronal signal processing approach is based on a tensor data analysis. It allows simultaneous treatment of the signal in several domains, (frequency, temporal, and spatial). Before applying the BCI platform to patients, a set of preclinical experiments are carried out on male Macaque Rhesus. Ethical approval was obtained from ComEth in accordance with the European Communities Council Directive of 1986 (86/609/EEC) for care of laboratory animals. High performance decoding of the continuous three-dimensional hand trajectory from epidural ECoG signals of the primate’s brain allows reproducing the arm movement by the exoskeleton arm (EMY) in real time. To ensure future clinical applications, algorithms were also tested in control human subjects, in noninvasive MEG acquisition system while they were executing real or imagined hand movements. Finally, the clinical research protocol submission to the French regulatory bodies is in progress. Applications of the BCI platform to post stroke patient rehabilitation are also investigated References [1] C. Mestais, G. Charvet, F. Sauter-Starace, M. Foerster, D. Ratel, and AL. Benabid, “WIMAGINE: Wireless 64-Channel ECoG Recording Implant for Long Term Clinical Applications”, IEEE Trans Neural Syst Rehabil Eng. 2015 Jan;23(1):10-21. [2] Y. Perrot, A. Verney, B. Morinière, and P. Garrec, "EMY: Full-body Exoskeleton," in ACM SIGGRAPH Emerging Technologies, Anaheim, USA, 2013. [3] A. Eliseyev and T. Aksenova, “Stable and artifact-resistant decoding of 3D hand trajectories from ECoG signals using the generalized additive model”, J. Neural Eng. 11 (2014) 066005 (13pp) [4] A. Eliseyev and T. Aksenova, "Recursive N-way partial least squares for brain-computer interface" PLoS One, vol. 8, p. e69962, 2013. The goal of CLINATEC® Brain Computer Interface Project is to improve tetraplegic subjects’ quality of life by allowing them to interact with their environment through the control of effectors with multiple degrees of freedom after training. Thanks to a long-term wireless 64-channel ECoG recording implant WIMAGINE® (Wireless Implantable Multi-channel Acquisition system for Generic Interface with NEurons) [1] and an innovative signal processing, the subject should be able to control a 4-limb exoskeleton EMY (Enhancing MobilitY) [2]. The ECoG signals from the subject’s brain will be recorded and wirelessly transmitted to a base station by the WIMAGINE® implant. This implant is composed of an array of 64 biocompatible electrodes, a hermetic titanium case which houses electronic boards, biocompatible antennas for wireless transmission of the data, and a remote power supply. The WIMAGINE implant complies with implantable medical device standards. Innovative ECoG signal decoding algorithms will allow self-paced control of the exoskeleton by decoding the subject’s brain activity [3] [4]. The neuronal signal processing approach is based on a tensor data analysis. It allows simultaneous treatment of the signal in several domains, (frequency, temporal, and spatial). Before applying the BCI platform to patients, a set of preclinical experiments are carried out on male Macaque Rhesus. Ethical approval was obtained from ComEth in accordance with the European Communities Council Directive of 1986 (86/609/EEC) for care of laboratory animals. High performance decoding of the continuous three-dimensional hand trajectory from epidural ECoG signals of the primate’s brain allows reproducing the arm movement by the exoskeleton arm (EMY) in real time. To ensure future clinical applications, algorithms were also tested in control human subjects, in noninvasive MEG acquisition system while they were executing real or imagined hand movements. Finally, the clinical research protocol submission to the French regulatory bodies is in progress. Applications of the BCI platform to post stroke patient rehabilitation are also investigated References [1] C. Mestais, G. Charvet, F. Sauter-Starace, M. Foerster, D. Ratel, and AL. Benabid, “WIMAGINE: Wireless 64-Channel ECoG Recording Implant for Long Term Clinical Applications”, IEEE Trans Neural Syst Rehabil Eng. 2015 Jan;23(1):10-21. [2] Y. Perrot, A. Verney, B. Morinière, and P. Garrec, "EMY: Full-body Exoskeleton," in ACM SIGGRAPH Emerging Technologies, Anaheim, USA, 2013. [3] A. Eliseyev and T. Aksenova, “Stable and artifact-resistant decoding of 3D hand trajectories from ECoG signals using the generalized additive model”, J. Neural Eng. 11 (2014) 066005 (13pp) [4] A. Eliseyev and T. Aksenova, "Recursive N-way partial least squares for brain-computer interface" PLoS One, vol. 8, p. e69962, 2013. The goal of CLINATEC® Brain Computer Interface Project is to improve tetraplegic subjects’ quality of life by allowing them to interact with their environment through the control of effectors with multiple degrees of freedom after training. Thanks to a long-term wireless 64-channel ECoG recording implant WIMAGINE® (Wireless Implantable Multi-channel Acquisition system for Generic Interface with NEurons) [1] and an innovative signal processing, the subject should be able to control a 4-limb exoskeleton EMY (Enhancing MobilitY) [2]. The ECoG signals from the subject’s brain will be recorded and wirelessly transmitted to a base station by the WIMAGINE® implant. This implant is composed of an array of 64 biocompatible electrodes, a hermetic titanium case which houses electronic boards, biocompatible antennas for wireless transmission of the data, and a remote power supply. The WIMAGINE implant complies with implantable medical device standards. Innovative ECoG signal decoding algorithms will allow self-paced control of the exoskeleton by decoding the subject’s brain activity [3] [4]. The neuronal signal processing approach is based on a tensor data analysis. It allows simultaneous treatment of the signal in several domains, (frequency, temporal, and spatial). Before applying the BCI platform to patients, a set of preclinical experiments are carried out on male Macaque Rhesus. Ethical approval was obtained from ComEth in accordance with the European Communities Council Directive of 1986 (86/609/EEC) for care of laboratory animals. High performance decoding of the continuous three-dimensional hand trajectory from epidural ECoG signals of the primate’s brain allows reproducing the arm movement by the exoskeleton arm (EMY) in real time. To ensure future clinical applications, algorithms were also tested in control human subjects, in noninvasive MEG acquisition system while they were executing real or imagined hand movements. Finally, the clinical research protocol submission to the French regulatory bodies is in progress. Applications of the BCI platform to post stroke patient rehabilitation are also investigated References [1] C. Mestais, G. Charvet, F. Sauter-Starace, M. Foerster, D. Ratel, and AL. Benabid, “WIMAGINE: Wireless 64-Channel ECoG Recording Implant for Long Term Clinical Applications”, IEEE Trans Neural Syst Rehabil Eng. 2015 Jan;23(1):10-21. [2] Y. Perrot, A. Verney, B. Morinière, and P. Garrec, "EMY: Full-body Exoskeleton," in ACM SIGGRAPH Emerging Technologies, Anaheim, USA, 2013. [3] A. Eliseyev and T. Aksenova, “Stable and artifact-resistant decoding of 3D hand trajectories from ECoG signals using the generalized additive model”, J. Neural Eng. 11 (2014) 066005 (13pp) [4] A. Eliseyev and T. Aksenova, "Recursive N-way partial least squares for brain-computer interface" PLoS One, vol. 8, p. e69962, 2013.

Acknowledgements

The BCI project was supported by French National Research Agency (ANR-Carnot Institute), Fondation Motrice, Fondation Nanosciences, Fondation de l’Avenir, and Fondation Philanthropique Edmond J. Safr

Keywords: Brain computer interface (BCI), exoskeleton, ECoG-recording implant, WIMAGINE, Tetraplegic

Conference: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015), Tokyo, Japan, 13 Mar - 15 Mar, 2015.

Presentation Type: Poster 4-5

Topic: Clinical Brain-Machine Interfaces

Citation: Mestais C, Charvet G, Sauter-Starace F, Abroug N, Arizumi N, Cokgungor S, Costecalde T, Foerster M, Morinière B, Pradal J, Ratel D, Rohu V, Schaeffer M, Tarrin N, Torres Martinez NR, Verney A, Yelisyeyev A, Aksenova T and Benabid AL (2015). Brain Computer Interface human platform to control a 4-limb exoskeleton based on the ECoG-recording implant WIMAGINE®: preliminary results. Conference Abstract: 2015 International Workshop on Clinical Brain-Machine Interfaces (CBMI2015). doi: 10.3389/conf.fnhum.2015.218.00020

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 23 Apr 2015; Published Online: 29 Apr 2015.

* Correspondence: Dr. Corinne Mestais, CEA/LETI, MINATEC Campus, Grenoble, France, corinne.mestais@cea.fr

© 2007 - 2020 Frontiers Media S.A. All Rights Reserved