Main Catalog Medical sciences Medical equipment and devices

Application of fingers vibrotactile stimulation in the brain — computer interface for the rehabilitation of post-stroke patients

Authors: Gremitsky I.S., Kuleshov D.Yu., Popova V.A.
Published in issue: #11(64)/2021
DOI: 10.18698/2541-8009-2021-11-746
Category: Medical sciences \| Chapter: Medical equipment and devices
Keywords: stroke, rehabilitation, brain-computer interface, sensory sensitivity, electroencephalography, evoked potentials, P300, vibrotactile stimulation, coherent averaging
Published: 17.11.2021

The paper presents an overview of modern brain-computer interfaces (BCIs) with vibrotactile stimulation. This technology can help the rehabilitation of patients with motor and visual impairments, since it involves only sensory sensitivity bypassing the visual pathway. The authors made a review of the literature devoted to the study of impaired sensory sensitivity in post-stroke patients. In this paper, the possibility was considered of recording the P300 evoked potentials under different modes of fingers stimulation with the help of vibrotactile motors. The numerical characteristics of P300 and high-quality images of the control BCI signal are shown. The data obtained require verification in further research.

References

[1] Fadeev P.A. Insul’t. Dostupno i dostoverno [A stroke. Easily and trustworthy]. Moscow, Mir i obrazovanie Publ., 2008 (in Russ.).

[2] Calabrò R.S., Naro A., Russo M. et al. Is two better than one? Muscle vibration plus robotic rehabilitation to improve upper limb spasticity and function: a pilot randomized controlled trial. PloS One, 2017, vol. 12, no. 10, art. e0185936. DOI: https://doi.org/10.1371/journal.pone.0185936

[3] Kübler A., Kotchoubey B., Kaiser J. et al. Brain–computer communication: unlocking the locked in. Psychol. Bull., 2001, vol. 127, no. 3, pp. 358–375. DOI: https://doi.org/10.1037//0033-2909.127.3.358

[4] Nagel S., Spüler M. World’s fastest brain-computer interface: combining EEG2Code with deep learning. PloS One, 2019, vol. 14, no. 9, art. e0221909. DOI: https://doi.org/10.1371/journal.pone.0221909

[5] Bradberry T.J., Gentili R.J., Contreras-Vidal J.L. Reconstructing three-dimensional hand movements from noninvasive electroencephalographic signals. J. Neurosci., 2010, vol. 30, no. 9, pp. 3432–3437. DOI: https://doi.org/10.1523/JNEUROSCI.6107-09.2010

[6] Birbaumer N., Hinterberger T., Kubler A. et al. The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome. IEEE Trans. Neural Syst. Rehabil. Eng., 2003, vol. 11, no. 2, pp. 120–123. DOI: https://doi.org/10.1109/TNSRE.2003.814439

[7] Farwell L.A., Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr. Clin .Neurophysiol., 1988, vol. 70, no. 6, pp. 510–523. DOI: https://doi.org/10.1016/0013-4694(88)90149-6

[8] Lenhardt A., Kaper M., Ritter H.J. An adaptive P300-based online brain–computer interface. IEEE Trans. Neural Syst. Rehabil. Eng., 2008, vol. 16, no. 2, pp. 121–130. DOI: https://doi.org/10.1109/TNSRE.2007.912816

[9] Allison B.Z., Kübler A., Jin J. 30+ years of P300 brain–computer interfaces. Psychophysiology, 2020, vol. 57, no. 7, art. e13569. DOI: https://doi.org/10.1111/psyp.13569

[10] Liburkina S.P., Vasil’yev A.N., Kaplan A.Ya. et al. Brain-computer interface-based motor imagery training for patients with neurological movement disorders. Zhurnal nevrologii i psikhiatrii im. SS Korsakova [S.S. Korsakov Journal of Neurology and Psychiatry], 2018, vol. 118, no. 9-2, pp. 63–68. DOI: https://doi.org/10.17116/jnevro201811809263 (in Russ.).

[11] Guger C., Spataro R., Pellas F. et al. Assessing command-following and communication with vibro-tactile P300 brain-computer interface tools in patients with unresponsive wakefulness syndrome. Front. Neurosci., 2018, vol. 12, art. 423. DOI: https://doi.org/10.3389/fnins.2018.00423

[12] Heilinger A., Ortner R., La Bella V. et al. Performance differences using a vibro-tactile P300 BCI in LIS-patients diagnosed with stroke and ALS. Front. Neurosci., 2018, vol. 12, art. 514. DOI: https://doi.org/10.3389/fnins.2018.00514

[13] Tyson S.F., Hanley M., Chillala J. et al. Sensory loss in hospital-admitted people with stroke: characteristics, associated factors, and relationship with function. Neurorehabil. Neural Repair, 2008, vol. 22, no. 2, pp. 166–172. DOI: https://doi.org/10.1177/1545968307305523

[14] Kessner S.S., Schlemm E., Cheng B. et al. Somatosensory deficits after ischemic stroke: time course and association with infarct location. Stroke, 2019, vol. 50, no. 5, pp. 1116–1123. DOI: https://doi.org/10.1161/STROKEAHA.118.023750

[15] Tarasenko I.A., P’yavchenko G.A., Mityaeva E.V. Tactile sensitivity of the skin of fingers in the age aspect and for some diseases. Zhurnal nauchnykh statey zdorov’ye i obrazovanie v XXI veke [The Journal of Scientific Articles Health and Education Millennium], 2012, vol. 14, no. 2, pp. 157–158 (in Russ.).

[16] Rinderknecht M.D. et al. Automated and quantitative assessment of tactile mislocalization after stroke. Front. Neurol., 2019, vol. 10, art. 593. DOI: https://doi.org/10.3389/fneur.2019.00593

[17] Neuron-Spectrum-5. neurosoft.com: website. URL: https://neurosoft.com/en/catalog/eeg/neuron-spectrum-5/ (accessed: 15.10.2021).

[18] The installation of the product. platan.ru: website. URL: https://doc.platan.ru/pdf/ec2009_QX.pdf (accessed: 15.10.2021).

[19] Mao Y. et al. The influence of visual attention on the performance of a novel tactile p300 brain-computer interface with cheeks-stim paradigm. Int. J. Neural Syst., 2021, vol. 31, no. 4, art. 2150004. DOI: https://doi.org/10.1142/s0129065721500040