Skip to main content

A Pilot Study of Brain-Triggered Electrical Stimulation with Visual Feedback in Patients with Incomplete Spinal Cord Injury

Journal of Medical and Biological Engineering volume 38, pages 790–803 (2018)Cite this article

Abstract

Improvement of upper extremity function is one of the greatest needs in patients with tetraplegia. Functional electrical stimulation (FES) directly controlled by the patient’s intention, through a brain–machine interface (BMI), could be used with a rehabilitative purpose. To date, there is scarce evidence about the feasibility of these systems in patients with incomplete spinal cord injury (iSCI), as studies usually focus on assistive technologies for complete injuries. The aim of this work is to design a system combining BMI, FES and realistic visual feedback, and test its feasibility as a therapeutic tool for hand rehabilitation of iSCI patients. A system integrating a BMI with FES and visual realistic feedback was developed as a neurorehabilitation tool. Movement-related cortical potentials and event-related desynchronization were used as features and a sparse discriminant analysis (SDA) to classify between rest and motor attempt. Four patients with iSCI performed five therapy sessions with that system in one of their hands only. Initial and final clinical assessments were fulfilled, as well as usability and exertion tests. The system showed a high accuracy, with an average success of 79.13% in rewarding the patients according to their brain activity. There were higher improvements of their prehension in the stimulated hand than in the non-stimulated. All patients reported that they would like to use this application in therapy and they felt very motivated. Our results suggest the feasibility of this integration of technologies to be considered as a therapeutic tool for upper limb rehabilitation. The results, despite being preliminary, provide promising insights for the use of BMI rehabilitation in incomplete SCI patients.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. Wyndaele, M., & Wyndaele, J.-J. (2006). Incidence, prevalence and epidemiology of spinal cord injury: What learns a worldwide literature survey? Spinal Cord, 44(9), 523–529.

    Article  Google Scholar 

  2. Harvey, L., Batty, J., Jones, R., & Crosbie, J. (2001). Hand function of C6 and C7 tetraplegics 1–16 years following injury. Spinal Cord, 39(1), 37–43.

    Article  Google Scholar 

  3. Snoek, G., IJzerman, M. J., Hermens, H., 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.

    Article  Google Scholar 

  4. French, J. S., Anderson-Erisman, K. D., & Sutter, M. (2010). What do spinal cord injury consumers want? A review of spinal cord injury consumer priorities and neuroprosthesis from the 2008 neural interfaces conference. Neuromodulation: Journal of the International Neuromodulation Society, 13(3), 229–231.

    Article  Google Scholar 

  5. Peckham, P. H., Keith, M. W., Kilgore, K. L., Grill, J. H., Wuolle, K. S., Thrope, G. B., et al. (2001). Efficacy of an implanted neuroprosthesis for restoring hand grasp in tetraplegia: A multicenter study. Archives of Physical Medicine and Rehabilitation, 82(10), 1380–1388.

    Article  Google Scholar 

  6. Barsi, G. I., Popovic, D. B., Tarkka, I. M., Sinkjær, T., & Grey, M. J. (2008). Cortical excitability changes following grasping exercise augmented with electrical stimulation. Experimental Brain Research, 191(1), 57–66.

    Article  Google Scholar 

  7. Knutson, J. S., Fu, M. J., Sheffler, L. R., & Chae, J. (2015). Neuromuscular electrical stimulation for motor restoration in Hemiplegia. Physical Medicine and Rehabilitation Clinics of North America., 26(4), 729.

    Article  Google Scholar 

  8. Pool, D., Blackmore, A. M., Bear, N., & Valentine, J. (2014). Effects of short-term daily community walk aide use on children with unilateral spastic cerebral palsy. Pediatric Physical Therapy, 26(3), 308–317.

    Article  Google Scholar 

  9. McGie, S. C., Zariffa, J., Popovic, M. R., & Nagai, M. K. (2015). Short-term neuroplastic effects of brain-controlled and muscle-controlled electrical stimulation. Neuromodulation: Journal of the International Neuromodulation Society, 18(3), 233–240.

    Article  Google Scholar 

  10. Pfurtscheller, G., Müller, G. R., Pfurtscheller, J., Gerner, H. J., & Rupp, R. (2003). “Thought”—control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neuroscience Letters, 351(1), 33–36.

    Article  Google Scholar 

  11. Rohm, M., Schneiders, M., Müller, C., Kreilinger, A., Kaiser, V., Müller-Putz, G. R., et al. (2013). Hybrid brain–computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury. Artificial Intelligence in Medicine, 59(2), 133–142.

    Article  Google Scholar 

  12. Kreilinger, A., Kaiser, V., Rohm, M., Rupp, R., & Müller-Putz, G. R. (2013). BCI and FES training of a spinal cord injured end-User to control a neuroprosthesis. Biomedizinische Technik, 58, 58–59.

    Google Scholar 

  13. Bunge, R., Puckett, W., Becerra, J., Marcillo, A., & Quencer, R. (1993). Observations on the pathology of spinal cord injury. Advances in Neurology, 59, 75–89.

    Google Scholar 

  14. Birbaumer, N., & Cohen, L. G. (2007). Brain–computer interfaces: Communication and restoration of movement in paralysis. The Journal of Physiology, 579(Pt 3), 621–636.

    Article  Google Scholar 

  15. Grosse-Wentrup, M., Mattia, D., & Oweiss, K. (2011). Using brain–computer interfaces to induce neural plasticity and restore function. Journal of Neural Engineering, 8(2), 25004.

    Article  Google Scholar 

  16. Sheffler, L. R., & Chae, J. (2007). Neuromuscular electrical stimulation in neurorehabilitation. Muscle and Nerve, 35(5), 562–590.

    Article  Google Scholar 

  17. Ramos-Murguialday, A., Broetz, D., Rea, M., Läer, L., Yilmaz, Ö., Brasil, F. L., et al. (2013). Brain–machine interface in chronic stroke rehabilitation: A controlled study. Annals of Neurology, 74(1), 100–108.

    Article  Google Scholar 

  18. Chung, E., Park, S.-I., Jang, Y.-Y., & Lee, B. H. (2015). Effects of brain–computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: Preliminary results. Journal of Physical Therapy Science, 27, 513–516.

    Article  Google Scholar 

  19. Li, M., Liu, Y., Wu, Y., Liu, S., Jia, J., & Zhang, L. (2014). Neurophysiological substrates of stroke patients with motor imagery-based brain–computer interface training. The International Journal of Neuroscience, 124(6), 403–415.

    Article  Google Scholar 

  20. Marino, R. J., Barros, T., Biering-Sorensen, F., Burns, S. P., Donovan, W. H., Graves, D. E., et al. (2003). International standards for neurological classification of spinal cord injury. Journal of Spinal Cord Medicine, 26, 50–56.

    Article  Google Scholar 

  21. Vučković, A., Wallace, L., & Allan, D. B. (2015). Hybrid brain–computer interface and functional electrical stimulation for sensorimotor training in participants with tetraplegia: A proof-of-concept study. Journal of Neurologic Physical Therapy: JNPT, 39(1), 3–14.

    Article  Google Scholar 

  22. King, C. E., Wang, P. T., McCrimmon, C. M., Chou, C. C., Do, A. H., & Nenadic, Z. (2015). The feasibility of a brain–computer interface functional electrical stimulation system for the restoration of overground walking after paraplegia. Journal of NeuroEngineering and Rehabilitation, 12(1), 80.

    Article  Google Scholar 

  23. Osuagwu, B. C. A., Wallace, L., Fraser, M., & Vuckovic, A. (2016). Rehabilitation of hand in subacute tetraplegic patients based on brain computer interface and functional electrical stimulation: A randomised pilot study. Journal of Neural Engineering, 13(6), 65002.

    Article  Google Scholar 

  24. Turner, D. L., Ramos-Murguialday, A., Birbaumer, N., Hoffmann, U., & Luft, A. (2013). Neurophysiology of robot-mediated training and therapy: A perspective for future use in clinical populations. Frontiers in Neurology, 4, 184.

    Article  Google Scholar 

  25. Lynch, C., & Popovic, M. R. (2008). Functional electrical stimulation. IEEE Control Systems, 28(2), 40–50.

    MathSciNet  Article  Google Scholar 

  26. Lohse, K., Shirzad, N., Verster, A., Hodges, N., & Van der Loos, H. F. M. (2013). Video games and rehabilitation: Using design principles to enhance engagement in physical therapy. Journal of Neurologic Physical Therapy, 37(4), 166–175.

    Article  Google Scholar 

  27. Hinterberger, T., Neumann, N., Pham, M., Kübler, A., Grether, A., Hofmayer, N., et al. (2004). A multimodal brain-based feedback and communication system. Experimental Brain Research, 154(4), 521–526.

    Article  Google Scholar 

  28. Donati, A. R. C., Shokur, S., Morya, E., Campos, D. S. F., Moioli, R. C., Gitti, C. M., et al. (2016). Long-term training with a brain–machine interface-based gait protocol induces partial neurological recovery in paraplegic patients. Scientific Reports, 6(April), 30383.

    Article  Google Scholar 

  29. Kirshblum, S. C., Waring, W., Biering-Sorensen, F., Burns, S. P., Johansen, M., Schmidt-Read, M., et al. (2011). Reference for the 2011 revision of the international standards for neurological classification of spinal cord injury. The Journal of Spinal Cord Medicine, 34(6), 547–554.

    Article  Google Scholar 

  30. Daniels, B., & Worthingbam, C. (1974). Muscle testing, techniques of manual examination. American Journal of Physical Medicine and Rehabilitation, 53(5), 241.

    Google Scholar 

  31. Bohannon, R. W., & Smith, M. B. (1987). Interrater reliability of a modified ashworth scale of muscle spasticity. Physical Therapy, 67, 206–207.

    Article  Google Scholar 

  32. 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. Journal of Neuroengineering and Rehabilitation, 11, 153–167.

    Article  Google Scholar 

  33. López-Larraz, E., Trincado-Alonso, F., Rajasekaran, V., Del-Ama, A. J., Aranda, J., Minguez, J., et al. (2016). Control of an ambulatory exoskeleton with a brain–machine interface for spinal cord injury gait rehabilitation. Frontiers in Neuroscience, 10, 359.

    Article  Google Scholar 

  34. Maeder, C. L., Sannelli, C., Haufe, S., & Blankertz, B. (2012). Pre-stimulus sensorimotor rhythms influence brain–computer interface classification performance. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(5), 653–662.

    Article  Google Scholar 

  35. Pfurtscheller, G., & Andrew, C. (1999). Event-related changes of band power and coherence: Methodology and interpretation. Journal of Clinical Neurophysiology, 16(6), 512–519.

    Article  Google Scholar 

  36. Shibasaki, H., & Hallett, M. (2006). What is the Bereitschaftspotential? Clinical Neurophysiology, 117(11), 2341–2356.

    Article  Google Scholar 

  37. Ibáñez, J., Serrano, J. I., del Castillo, M. D., Monge-Pereira, E., Molina-Rueda, F., Alguacil-Diego, I., et al. (2014). Detection of the onset of upper-limb movements based on the combined analysis of changes in the sensorimotor rhythms and slow cortical potentials. Journal of Neural Engineering, 11(5), 56009.

    Article  Google Scholar 

  38. Bos, R., De Waele, S., & Broersen, P. M. T. (2002). Autoregressive spectral estimation by application of the Burg algorithm to irregularly sampled data. IEEE Transactions on Instrumentation and Measurement, 51(6), 1289–1294.

    Article  Google Scholar 

  39. Costa, Á., Iáñez, E., Úbeda, A., Hortal, E., Del-Ama, A. J., Gil-Agudo, Á., et al. (2016). Decoding the attentional demands of gait through EEG gamma band features. PLoS ONE, 11(4), e0154136.

    Article  Google Scholar 

  40. Garipelli, G., Chavarriaga, R., Del, R., & Millán, J. (2013). Single trial analysis of slow cortical potentials: A study on anticipation related potentials. Journal of Neural Engineering, 10(3), 36014.

    Article  Google Scholar 

  41. Clemmensen, L., Hastie, T., Witten, D., & Ersbøll, B. (2011). Sparse discriminant analysis. Technometrics, 53(4), 406–413.

    MathSciNet  Article  Google Scholar 

  42. López-Larraz, E., Ibáñez, J., Trincado-Alonso, F., Monge-Pereira, E., Pons, J. L., & Montesano, L. (2017). Comparing recalibration strategies for electroencephalography-based decoders of movement intention in neurological patients with motor disability. International journal of Neural Systems: In Press.

    Google Scholar 

  43. Fekete, C., Eriks-Hoogland, I., Baumberger, M., Catz, A., Itzkovich, M., Lüthi, H., et al. (2013). Development and validation of a self-report version of the spinal cord independence measure (SCIM III). Spinal Cord, 51(1), 40–47.

    Article  Google Scholar 

  44. Kalsi-Ryan, S., Curt, A., Fehlings, M. G., & Verrier, M. C. (2009). Assessment of the hand in tetraplegia using the graded redefined assessment of strength, sensibility and prehension (GRASSP). Topics in Spinal Cord Injury Rehabilitation, 14(4), 34–46.

    Article  Google Scholar 

  45. Lange, B., Flynn, S., Proffitt, R., Chang, C.-Y., & Rizzo, A. S. (2010). Development of an interactive game-based rehabilitation tool for dynamic balance training. Topics in Stroke Rehabilitation, 17(5), 345–352.

    Article  Google Scholar 

  46. Borg, G. (1970). Perceived exertion as an indicator of somatic stress. Candinavian Journal of Rehabilitation Medicine, 2(2), 92.

    Google Scholar 

  47. López-Larraz, E., Trincado-Alonso, F., & Montesano, L. (2015). Brain–machine interfaces for motor rehabilitation: Is recalibration important? In IEEE International Conference on Rehabilitation Robotics (ICORR) (pp. 223–228).

  48. Takahashi, M., Takeda, K., Otaka, Y., Osu, R., Hanakawa, T., Gouko, M., et al. (2012). Event related desynchronization-modulated functional electrical stimulation system for stroke rehabilitation: A feasibility study. Journal of Neuroengineering and Rehabilitation, 9(1), 56.

    Article  Google Scholar 

  49. Miralles, F., Vargiu, E., Dauwalder, S., Solà, M., Müller-putz, G., Wriessnegger, S. C., et al. (2015). Brain computer interface on track to home. The Scientific World Journal, 2015, 17.

    Article  Google Scholar 

  50. Krakauer, J. W. (2006). Motor learning: Its relevance to stroke recovery and neurorehabilitation. Current Opinion in Neurology, 19, 84–90.

    Article  Google Scholar 

  51. Ring, H., & Rosenthal, N. (2005). Controlled study of neuroprosthetic functional electrical stimulation in sub-acute post-stroke rehabilitation. Journal of Rehabilitation Medicine, 37(1), 32–36.

    Article  Google Scholar 

  52. López-Larraz, E., Montesano, L., Gil-Agudo, Á., Minguez, J., & Oliviero, A. (2015). Evolution of EEG motor rhythms after spinal cord injury: A longitudinal study. PLoS ONE, 10(7), e0131759.

    Article  Google Scholar 

  53. López-Larraz, E., Antelis, J. M., Montesano, L., Gil-Agudo, A., & Minguez, J. (2012). Continuous decoding of motor attempt and motor imagery from EEG activity in spinal cord injury patients. Conference proceedings: …Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2012, (pp. 1798–801).

  54. Patil, S., Raza, W., Jamil, F., Caley, R., & O’Connor, R. (2014). Functional electrical stimulation for the upper limb in tetraplegic spinal cord injury: A systematic review. Journal of Medical Engineering & Technology, 39(7), 419–423.

    Article  Google Scholar 

  55. Rupp, R. (2014). Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury. Frontiers in Neuroengineering, 7(September), 38.

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank V. Rajasekaran for his contributions to the grammar correction of the article. This work was supported by the Spanish Ministry of Economy and Competitiveness [Projects HYPER-CSD2009-00067 CONSOLIDER-INGENIO 2010, DGA-FSE (grupo T04) and DPI 2011-25892]. E. López-Larraz was supported by the Fortüne Program of the University of Tübingen (2422-0-0) and the BMBF Projects FKZ 13GW0053 and FKZ 16SV7754. Each of the authors has read and concurs with the content in the final manuscript. The contributing authors guarantee that this manuscript has not been submitted, nor published elsewhere.

Author information

Authors and Affiliations

  1. Biomechanics and Technical Aids Unit, National Hospital for Spinal Cord Injury, Finca La Peraleda S/N, 45071, Toledo, Spain

    Fernando Trincado-Alonso, Soraya Pérez-Nombela & Ángel Gil-Agudo

  2. Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Otfried-Müller-Straße, 25, 72076, Tübingen, Germany

    Eduardo López-Larraz

  3. Neural Rehabilitation Group, Spanish National Research Council (CSIC), Avda. Doctor Arce, 37, 28002, Madrid, Spain

    Francisco Resquín & José Luis Pons

  4. Vicomtech-IK4, Parque Tecnológico de San Sebastián, Mikeletegi Pasealekua 57, 20009, Donostia-San Sebastián, Spain

    Aitor Ardanza

  5. Departamento de Informática e Ingeniería de Sistemas, University of Zaragoza, Saragossa, Spain

    Luis Montesano

  6. Instituto de Investigación en Ingeniería de Aragón (I3A), C/María de Luna no 1, 50018, Saragossa, Spain

    Luis Montesano

Authors
  1. Fernando Trincado-Alonso
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eduardo López-Larraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francisco Resquín
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aitor Ardanza
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Soraya Pérez-Nombela
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. José Luis Pons
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Luis Montesano
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ángel Gil-Agudo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fernando Trincado-Alonso.

Ethics declarations

Conflict of interest

Each of the authors declares that they do not have any financial and non-financial competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Trincado-Alonso, F., López-Larraz, E., Resquín, F. et al. A Pilot Study of Brain-Triggered Electrical Stimulation with Visual Feedback in Patients with Incomplete Spinal Cord Injury. J. Med. Biol. Eng. 38, 790–803 (2018). https://doi.org/10.1007/s40846-017-0343-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40846-017-0343-0

Keywords

  • Spinal cord injury
  • Brain–machine interface
  • Neurorehabilitation
  • Functional electrical stimulation