Abstract
Restoration of grasping has the highest priority for people with cervical spinal cord injury (SCI). This chapter describes the non-invasive brain–computer interface (BCI)-controlled grasp neuroprosthesis developed within the European Horizon 2020 project MoreGrasp. Based on former projects of the collaborators, several innovative technologies were developed within the MoreGrasp project with the aim to achieve an intuitive thought-controlled restoration of hand function in end users with tetraplegia for supporting activities of daily living. The end users in the focus of this project have been people with sufficiently preserved elbow and shoulder movements, but missing hand and finger functions.
In particular, within MoreGrasp a novel, closed-loop upper limb grasp neuroprosthesis was developed which could be controlled by different multimodal control options, namely user-friendly BCIs based on gel-less electrodes and wireless electroencephalogram (EEG) amplifiers using natural movement attempt strategies, a shoulder joystick and instrumented objects. All these control modalities could be tailored to the end users’ needs and capabilities. Furthermore, a web-based service infrastructure for registration, assessment, and training of end users was developed. It assisted experimenters as well as end users in prototype assessment and operation. Finally, a clinical study involving end users with tetraplegia evaluating the MoreGrasp technology at their homes was initiated. The first results obtained and the lessons learned are provided at the end of the chapter.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agashe HA, Paek AY, Zhang Y, Contreras-Vidal JL (2015) Global cortical activity predicts shape of hand during grasping. Front Neurosci 9:121
Anderson KD (2004) Targeting recovery: priorities of the spinal cord-injured population. J Neurotrauma 21(10):1371–1383
ASIA and ISCoS International Standards Committee (2019) The 2019 revision of the international standards for neurological classification of spinal cord injury (ISNCSCI)—what’s new? Spinal Cord 57:815–817. https://doi.org/10.1038/s41393-019-0350-9
Blokland Y, Vlek R, Karaman B, Özin F, Thijssen D, Eijsvogels T, Colier W, Floor-Westerdijk M, Bruhn J, Farquhar J (2012) Detection of event-related desynchronization during attempted and imagined movements in tetraplegics for brain switch control. In: Conference Proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 2012. IEEE, San Diego, CA, pp 3967–3969
Carlson T, Monnard G, Leeb R, del Millan J (2011) Evaluation of proportional and discrete shared control paradigms for low resolution user inputs. In: 2011 IEEE International conference on systems, man, and cybernetics. IEEE, New York. https://doi.org/10.1109/icsmc.2011.6083812
Dremstrup K, Niazi IK, Jochumsen M, Jiang N, Mrachacz-Kersting N, Farina D (2014) Rehabilitation using a brain computer interface based on movement related cortical potentials—a review. In: IFMBE Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-00846-2_409
Friedrich EVC, Neuper C, Scherer R (2013) Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually. PLoS One 8(9):e76214
Iturrate I, Chavarriaga R, Pereira M, Zhang H, Corbet T, Leeb R, Millán JDR (2018) Human EEG reveals distinct neural correlates of power and precision grasping types. NeuroImage 181:635–644
Jochumsen M, Niazi IK, Mrachacz-Kersting N, Farina D, Dremstrup K (2013) Detection and classification of movement-related cortical potentials associated with task force and speed. J Neural Eng 10(5):056015
Kornhuber HH, Deecke L (1965) Hirnpotentialänderungen bei Willkürbewegungen und passiven Bewegungen des Menschen: Bereitschaftspotential und reafferente Potentiale. Pflüger’s Archiv für die gesamte Physiologie des Menschen und der Tiere 284:1–17. https://doi.org/10.1007/bf00412364
Kreilinger A, Kaiser V, Rohm M, Rupp R, Müller-Putz GR (2013) BCI and FES training of a spinal cord injured end-user to control a neuroprosthesis. Biomed Eng 58:1. https://doi.org/10.1515/bmt-2013-4443
Leclercq C, Lemouel M-A, Albert T (2005) Chirurgische funktionsverbesserung an der oberen extremität von tetraplegikern. Handchirurgie\Textperiodcentered Mikrochirurgie\Textperiodcentered Plastische Chirurgie 37(04):230–237
López-Larraz E, Montesano L, Gil-Agudo Á, Minguez J (2014) Continuous decoding of movement intention of upper limb self-initiated analytic movements from pre-movement EEG correlates. J Neuroeng Rehabilit 11:153
Medical Research Council, Nerve Injuries Committee; University of Edinburgh, Department of Surgery (1943) Aids to investigation of peripheral nerve injuries. Medical Research Council memorandum no. 7. Her Majesty’s Stationary Office, London
Müller-Putz GR, Scherer R, Pfurtscheller G, Rupp R (2005) EEG-based neuroprosthesis control: a step towards clinical practice. Neurosci Lett 382:169–174. https://doi.org/10.1016/j.neulet.2005.03.021
Muller-Putz G, Leeb R, Tangermann M, Hohne J, Kubler A, Cincotti F, Mattia D, Rupp R, Muller K-R, del Millan J (2015) Towards noninvasive hybrid brain–computer interfaces: framework, practice, clinical application, and beyond. Proc IEEE 103:926–943. https://doi.org/10.1109/jproc.2015.2411333
Muller-Putz GR, Ofner P, Pereira J, Pinegger A, Schwarz A, Zube M, Eck U, Hessing B, Schneiders M, Rupp R (2019) Applying intuitive EEG-controlled grasp neuroprostheses in individuals with spinal cord injury: preliminary results from the MoreGrasp clinical feasibility study. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Berlin. https://doi.org/10.1109/embc.2019.8856491
Müller-Putz GR, Ofner P, Pereira J, Pinegger A, Schwarz A, Zube M, Eck U, Hessing B, Schneiders M, Rupp R (2019) Applying intuitive EEG-controlled grasp neuroprostheses in individuals with spinal cord injury: preliminary results from the MoreGrasp clinical feasibility study. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Berlin, pp 5949–5955
Niazi IK, Jiang N, Tiberghien O, Nielsen JF, Dremstrup K, Farina D (2011) Detection of movement intention from single-trial movement-related cortical potentials. J Neural Eng 8(6):066009
Oda S, Moritani T (1995) Movement-related cortical potentials during handgrip contractions with special reference to force and electromyogram bilateral deficit. Eur J Appl Physiol Occup Physiol 72(1–2):1–5
Ofner P, Schwarz A, Pereira J, Müller-Putz GR (2017) Upper limb movements can be decoded from the time-domain of low-frequency EEG. PLoS One 12(8):e0182578
Ofner P, Schwarz A, Pereira J, Wyss D, Wildburger R, Müller-Putz GR (2019) Attempted arm and hand movements can be decoded from low-frequency EEG from persons with spinal cord injury. Sci Rep 9(1):7134
Omedes J, Schwarz A, Montesano L, Muller-Putz G (2017) Hierarchical decoding of grasping commands from EEG. In: Conference proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society Conference 2017 (July). IEEE, Seogwipo, pp 2085–2088
Pereira J, Ofner P, Schwarz A, Sburlea AI, Müller-Putz GR (2017) EEG neural correlates of goal-directed movement intention. NeuroImage 149:129–140
Pfurtscheller G (2010) The hybrid BCI. Front Neurosci. https://doi.org/10.3389/fnpro.2010.00003
Pfurtscheller G, Müller GR, Pfurtscheller J, Gerner HJ, Rupp R (2003) ‘Thought’—Control of functional electrical stimulation to restore hand grasp in a patient with Tetraplegia. Neurosci Lett 351:33–36. https://doi.org/10.1016/s0304-3940(03)00947-9
Pohl H, Murray-Smith R (2013) Focused and casual interactions. In: Proceedings of the SIGCHI conference on human factors in computing systems—CHI ’13. Association for Computing Machinery, New York. https://doi.org/10.1145/2470654.2481307
Rohm M, Schneiders M, Müller C, Kreilinger A, Kaiser V, Müller-Putz GR, Rupp R (2013) Hybrid brain-computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury. Artif Intell Med 59(2):133–142
Rupp R, Rohm M, Schneiders M, Weidner N, Kaiser V, Kreilinger A, Müller-Putz GR (2013) Think2grasp—BCI-controlled neuroprosthesis for the upper extremity. Biomed Tech 58:1. https://doi.org/10.1515/bmt-2013-4440
Rupp R, Rohm M, Schneiders M, Kreilinger A, Müller-Putz GR (2015) Functional rehabilitation of the paralyzed upper extremity after spinal cord injury by noninvasive hybrid neuroprostheses. Proc IEEE 103(6):954–968
Schwarz A, Ofner P, Pereira J, Sburlea AI, Müller-Putz GR (2018) Decoding natural reach-and-grasp actions from human EEG. J Neural Eng 15(1):016005
Schwarz A, Pereira J, Kobler R, Muller-Putz GR (2019) Unimanual and bimanual reach-and-grasp actions can be decoded from human EEG. IEEE Trans Biomed Eng. https://doi.org/10.1109/tbme.2019.2942974
Schwarz A, Escolano C, Montesano L, Müller-Putz G (2020a) Analyzing and decoding natural reach-and-grasp actions using gel, water and dry EEG systems. Front Neurosci 14:849ff
Schwarz A, Höller MK, Pereira J, Ofner P, Müller-Putz GR (2020b) Decoding hand movements from human EEG to control a robotic arm in a simulation environment. J Neural Eng 17(3):036010
Schwarz A, Pereira J, Kobler R, Muller-Putz GR (2020c) Unimanual and bimanual reach-and-grasp actions can be decoded from human EEG. IEEE Trans Biomed Eng 67(6):1684–1695
Sheridan TB (2002) Some musings on four ways humans couple: implications for systems design. In: IEEE transactions on systems, man, and cybernetics—Part A: systems and humans. IEEE, New York. https://doi.org/10.1109/3468.995525
Shibasaki H, Hallett M (2006) What is the bereitschaftspotential? Clin Neurophysiol 117:2341–2356. https://doi.org/10.1016/j.clinph.2006.04.025
Snoek GJ, IJzerman MJ, Hermens HJ, Maxwell D, Biering-Sorensen F (2004) Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics. Spinal Cord 42(9):526–532
Tonin L, Leeb R, Tavella M, Perdikis S, del Millan J (2010) The role of shared-control in BCI-based telepresence. In: 2010 IEEE International conference on systems, man and cybernetics. IEEE, Istanbul. https://doi.org/10.1109/icsmc.2010.5642338
van Zyl N, Hill B, Cooper C, Hahn J, Galea MP (2019) Expanding traditional tendon-based techniques with nerve transfers for the restoration of upper limb function in tetraplegia: a prospective case series. Lancet 394(10198):565–575
Williamson J, Murray-Smith R (2012) Rewarding the original. In: Proceedings of the 2012 ACM annual conference on human factors in computing systems—CHI ’12. Association for Computing Machinery, New York. https://doi.org/10.1145/2207676.2208301
Wuolle KS, Van Doren CL, Thrope GB, Keith MW, Peckham PH (1994) Development of a quantitative hand grasp and release test for patients with tetraplegia using a hand neuroprosthesis. J Hand Surg 19(2):209–218
Xu R, Jiang N, Vuckovic A, Hasan M, Mrachacz-Kersting N, Allan D, Fraser M et al (2014) Movement-related cortical potentials in paraplegic patients: abnormal patterns and considerations for BCI-rehabilitation. Front Neuroeng 7:35
Yang L, Yao L (2018) EEG neural correlates of self-paced left- and right-hand movement intention during a reaching task. In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Honolulu. https://doi.org/10.1109/embc.2018.8512725
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Müller-Putz, G. et al. (2021). Non-invasive Brain–Computer Interfaces for Control of Grasp Neuroprosthesis: The European MoreGrasp Initiative. In: Müller-Putz, G., Rupp, R. (eds) Neuroprosthetics and Brain-Computer Interfaces in Spinal Cord Injury. Springer, Cham. https://doi.org/10.1007/978-3-030-68545-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-68545-4_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-68544-7
Online ISBN: 978-3-030-68545-4
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)