Abstract
People with central nervous system injuries or damage usually present motor sequelae that limit their daily living activities and hence their quality of life; so they need neurorehabilitation therapies to improve their motor function. Functional Electrical Stimulators (FESs) are used to recover the grip and release of objects and/or the foot dorsiflexion during the gait, among others. A FES device produces or assists movements through the application of electrical stimuli to either mixed or sensory nerves. It is commanded by the patient when his/her motor intention is detected. Brain-Computer Interfaces (BCIs) are an emerging technology that has been proposed to facilitate the restoration of the affected motor functions. They record signals of electroencephalography, extract its most relevant features and, through a classifier, detect the patient’s intention to control an actuator device, such as a FES. In this chapter, the general structure and operation of BCIs which use surface FES as an actuator device is described. Two therapeutic applications of BCI-FES for motor neurorehabilitation of patients with stroke and multiple sclerosis are also described. In both studies, the patients showed improvement on motor functional outcomes which might have related to changes in their CNS. This encourages further research to elucidate the mechanisms that underlay and drive this motor recovery. These two application are examples of interdisciplinary collaboration between physicians and biomedical engineering researchers for presenting an emerging technological solution to improve patients quality of life. More studies focus on this direction are needed to realize the translation research to clinical practice.
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
References
Aguilar CB, Carrere LC, Tabernig CB (2020) Lower limb motor intention: ERD time-course analysis in stroke and healthy subjects. Rev Argentina Bioingenieria 23:19–23
Aldea R, Oana-Diana E (2013) Detecting sensorimotor rhythms from the EEG signals using the independent component analysis and the coefficient of determination. In: ISSCS 2013—international symposium signals, circuits system, pp 2–6. https://doi.org/10.1109/ISSCS.2013.6651213
Biasiucci A, Leeb R, Iturrate I et al (2018) Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun 9:2421–2434. https://doi.org/10.1038/s41467-018-04673-z
Bonzano L, Pedullà L, Tacchino A et al (2019) Upper limb motor training based on task-oriented exercises induces functional brain reorganization in patients with multiple sclerosis. Neuroscience 410:150–159. https://doi.org/10.1016/j.neuroscience.2019.05.004
Brunner C, Birbaumer N, Blankertz B et al (2015) BNCI Horizon 2020: towards a roadmap for the BCI community. Brain Comput Interfaces 1–10. https://doi.org/10.1080/2326263X.2015.1008956
Carrere LC, Escher LG, Tabernig CB (2020a) A wireless BCI-FES based on motor intent for lower limb rehabilitation. CLAIB 2019:1–9
Carrere LC, Taborda M, Ballario CH, Tabernig CB (2020b) A new approach for gait rehabilitation in multiple sclerosis based on brain computer interface and functional electrical stimulation. In: RIMS digital conference. Multiple sclerosis journal, pp 15–65
Carrere LC, Taborda M, Ballario CH, Tabernig CB (2021) A new approach for gait rehabilitation in multiple sclerosis based on BCI-FES: preliminary results (Press)
Cervera MA, Soekadar SR, Ushiba J et al (2018) Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis. Ann Clin Transl Neurol 5:651–663. https://doi.org/10.1002/acn3.544
Cheryl L, Popovic M (2008) Functional electrical stimulation. IEEE Control Syst Mag. https://doi.org/10.1109/MCS.2007.914689
Doucet BM, Lam A, Griffin L (2012) Neuromuscular electrical stimulation for skeletal muscle function. Yale J Biol Med 85:201
Emotiv E (2014) User manual-headset and software setup for your Emotiv EPOC neuroheadset. Emotiv
He J, Ma C, Herman R (2008) Engineering neural interfaces for rehabilitation of lower limb function in spinal cord injured. In: Proceedings of the IEEE, pp 1152–1166
Jeannerod M (1995) Mental imagery in the motor context. Neuropsychology 33:1419–1432
Jure FA, Carrere LC, Gentiletti GG, Tabernig CB (2016) BCI-FES system for neuro-rehabilitation of stroke patients. J Phys Conf Ser 705:1–4. https://doi.org/10.1088/1742-6596/705/1/012058
Lang M (2012) Investigating the Emotiv EPOC for cognitive control in limited training time
Legenstein R, Chase SM, Schwartz AB, Maass W (2010) A reward-modulated Hebbian learning rule can explain experimentally observed network reorganization in a brain control Task. J Neurosci 30:8400–8410. https://doi.org/10.1523/JNEUROSCI.4284-09.2010
Leocani L, Rovaris F, Martinelli-Boneschi P et al (2005) Movement preparation is affected by tissue damage in multiple sclerosis: evidence from EEG event-related desynchronization. Clin Neurophysiol 116:1515–1519. https://doi.org/10.1016/j.clinph.2005.02.026
Levin MF, Sveistrup H, Subramanian SK (2010) Feedback and virtual environments for motor learning and rehabilitation. Schedae 2:19–36
Li S, Francisco GE (2015) New insights into the pathophysiology of post-stroke spasticity. Front Hum Neurosci 9:1–9. https://doi.org/10.3389/fnhum.2015.00192
Lipp I, Tomassini V (2015) Neuroplasticity and motor rehabilitation in multiple sclerosis. Front Neurol 6. https://doi.org/10.3389/fneur.2015.00059
Malouin F, Richards CL (2010) Mental practice for relearning locomotor skills. Phys Ther 90:240–251. https://doi.org/10.2522/ptj.20090029
Miller L, McFadyen A, Lord AC et al (2017) Functional electrical stimulation for foot drop in multiple sclerosis: a systematic review and meta-analysis of the effect on gait speed. Arch Phys Med Rehabil 98:1435–1452. https://doi.org/10.1016/j.apmr.2016.12.007
Moritz CT, Perlmutter SI, Fetz EE (2008) Direct control of paralysed muscles by cortical neurons. Nature 456:639–642. https://doi.org/10.1038/nature07418
Neuper C, Pfurtscheller G (2010) Electroencephalographic characteristics during motor imagery. In: Aymeric G, Collet C (eds) The neurophysiological foundations of mental and motor imagery. University Press Scholarship Online Oxford, pp 45–66
O’Dell MW, Lin C-CD, Harrison V (2009) Stroke rehabilitation: strategies to enhance motor recovery. Annu Rev Med 60:55–68. https://doi.org/10.1146/annurev.med.60.042707.104248
Pfurtscheller G, Neuper C (2003) Movement and ERD/ERS. In: The Bereitschaftspotential, pp 191–206
Pfurtscheller G, Lopes da Silva FH (1999) Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110:1842–1857. https://doi.org/10.1016/S1388-2457(99)00141-8
Pfurtscheller G, Lopes da Silva FH (2011) EEG event-related desynchronization (ERD) and event-related synchronization (ERS). In: Schomer Donald L, da Silva FHL (ed) Niedermeyer’s electroencephalography: basic principles, clinical applications, and related fields, 6th edn. Lippincott Williams & Wilkins., Filadelfia, Pennsylvania, Estados Unidos, pp 937–948
Prosperini L, Di FM (2019) Beyond clinical changes: rehabilitation-induced neuroplasticity in MS. Mult Scler J 25:1348–1362. https://doi.org/10.1177/1352458519846096
Ramos-Murguialday A, Broetz D, Rea M et al (2013) Brain-machine-interface in chronic stroke rehabilitation: a controlled study. Ann Neurol 74:100–108. https://doi.org/10.1002/ana.23879
Scally JB, Baker JS, Rankin J et al (2020) Evaluating functional electrical stimulation (FES) cycling on cardiovascular, musculoskeletal and functional outcomes in adults with multiple sclerosis and mobility impairment: a systematic review. Mult Scler Relat Disord 37:101485. https://doi.org/10.1016/j.msard.2019.101485
Schalk G, Mellinger J (2010a) A practical guide to brain-computer interfacing with BCI2000: general-purpose software for brain-computer interface research, data acquisition, stimulus presentation, and brain monitoring. Springer, London
Schalk G, Mellinger J (2010b) A practical guide to brain-computer interfacing with BCI2000. Springer, New York
Springer S, Khamis S (2017) Effects of functional electrical stimulation on gait in people with multiple sclerosis—a systematic review. Mult Scler Relat Disord 13:4–12. https://doi.org/10.1016/j.msard.2017.01.010
Sternowski K, Perone K (2017) Uses of electrical stimulation for the rehabilitation of people with multiple sclerosis: a review. Curr Phys Med Rehabil Reports 5:121–133. https://doi.org/10.1007/s40141-017-0157-6
Tabernig CB (2018) Technology for motor rehabilitation based on the planning and execution of movements. PhD thesis, National University of Entre Ríos, Argentine
Tabernig CB, Spaich EG (2021) Functional electrical Stimulation for motor neurorehabilitation. In: Natalia L (ed) Advances in technology-assisted neurorehabilitation. Elsevier (Press)
Tabernig CB, Lopez CA, Carrere LC et al (2018) Neurorehabilitation therapy of patients with severe stroke based on functional electrical stimulation commanded by a brain computer interface. J Rehabil Assist Technol Eng 5:1–12
Tabernig C, Carrere LC, Gentiletti G, Spaich EG (2019) Post-stroke injured cerebral cortex: frequency analysis of the desynchronization of its sensorimotor rhythms during motor intent. In: IFMBE proceeding series. Springer
Tomassini V, Matthews PM, Thompson AJ et al (2012) Neuroplasticity and functional recovery in multiple sclerosis. Nat Rev Neurol 8:635–646. https://doi.org/10.1038/nrneurol.2012.179
Tyson SF, Crow JL, Connell L et al (2013) Sensory impairments of the lower limb after stroke: a pooled analysis of individual patient data. Top Stroke Rehabil 20:441–449. https://doi.org/10.1310/tsr2005-441
Winstein CJ, Stein J, Arena R et al (2016) Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals. Stroke 47:e98–e169
World Health Organization (2017) World Health Organization. In: World heal. Organ.web site
World Health Organization and Others (2008) Atlas: multiple sclerosis resources in the world 2008. World Health Organization
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Carrere, L.C., Ballario, C.H., Tabernig, C.B. (2022). Brain-Computer Interfaces with Functional Electrical Stimulation for Motor Neurorehabilitation: From Research to Clinical Practice. In: Simini, F., Bertemes-Filho, P. (eds) Medicine-Based Informatics and Engineering. Lecture Notes in Bioengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-87845-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-87845-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-87844-3
Online ISBN: 978-3-030-87845-0
eBook Packages: EngineeringEngineering (R0)