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Section BRAIN-COMPUTER INTERFACES, COGNITIVE NAVIGATION WORKSHOP AND NEUROENGINEERING
Acknowledgements
The research was supported by the Russian Foundation for Basic Research (grant 13-04-12067). References
1. T.A. Akopova, P.S. Timashev, T.S. Demina, K.N. Bardakova, N.V. Minaev, V.F. Burdukovskii, G.V. Cherkaev, L.V. Vladimirov, A.V. Istomin, E.A. Svidchenko, N.M. Surin, V.N. Bagratashvili, Solid-state synthesis of unsaturated chi-tosan derivatives to design 3D structures through two-photon-induced polymerization, Mendeleev Communications, 2015, 25, 280-282.
2. P.S. Timashev, T.S. Demina, N.V. Minaev, K.N. Bardakova, A.V. Koroleva, O.A. Kufelt, B.N. Chickov, V.Ya. Panchen-ko, T.A. Akopova, V.N. Bagratashvili Fabrication of microstructured materials based on chitosan and its derivatives using two-photon polymerization, High energy chemistry, 2015, 49 (4), 300-303.
3. O. Kufelt, A. El-Tamer, C. Sehring, S. Schlie-Wolter, and B. N. Chichkov, Hyaluronic Acid Based Materials for Scaffolding via Two-Photon Polymerization, Biomacromolecules, 2014, 15 (2), 650-659.
Development of Tactile Feedback Loop Based on Skin Vibro-Stimulation for Brain-Computer Interface
A. Pimashkin1 *, A. Motailo1, M. Shamshin1, S.Yu. Gordleeva1
Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia. * Presenting e-mail: pimaskin@neuro.nnov.ru
About 30% of stroke patients suffer from disorders of motor and somatosensory systems [1]. Methods of target rehabilitation of motor and sensory deficits are very important for recovery of these patients [2]. Conventional rehabilitation methods and approaches require a lot of specialized staff and are not enough effective, and for example, the United States spends $36.5 billion a year on it [3]. In this context the rehabilitation approaches based on BCI seem to be the most promising.
The main innovation of these approaches is that BCI allows you to decode the very intention to motion that occurs as a plan of action in the brain, even in deeply paralyzed people. This intention can be identified by the algorhytms and translated into a command for external executive devices: manipulators, exoskeletons, etc. Thus, human intent can be transformed into a real action even in case of strong damage of pathways between brain and the muscles. This will provide an opportunity for patients to control a training device directly by mental efforts that would make rehabilitation more effective and less demanding to support personnel.
However, despite the high level of modern development of BCI technology, including the latest advances of computer and electronic equipment, software and algorithmic approaches and neurophysiological knowledge, all these BCIs have several common disadvantages. These are low information transfer rate, very slow development and poor automation of the BCI skill. Moreover, it is impossible to control a BCI-operated object proportionally, for instance, smoothly move a cursor along the desired path. A few attempts to build a BCI feedback as a result of produced actions have been taken, some of them were successful, but all this was done either invasively or using animals [4].
Therefore, the aim of this work is to develop a suitable for human non-invasive BCI technology with nonvisual feedback loop. This young technology may help to overcome the existing BCIs restrictions in operation speed and accuracy, but which is more important, to make this technology closer to the real organism with its natural sensorimotor pathways and ability to automate new skills.
The relevance of this work is that the proposed new BCI technology for humans will include feedback by means of multi-unit vibro-tactile skin stimulation. This will help to build a BCI technology that can reproduce natural mechanisms of human motor activity by means of muscles that are initially provided by the feedback with the brain.
In this study we developed a circuit which consisted of 5 independent vibro-stimulators placed on the skin surface of the shoulder girdle. The vibromotors were driven by a microcontroller through serial port of the computer and used as a sensor feedback loop. We developed a software that can be used to translate any BCI command to each motor independently with specific vibrating pattern. Decoded patterns of motor movement in EEG experiments were translated into tactile commands to the skin. Each motor generated high-frequency vibration (9000 rpm) during short period (1 sec) after the movement pattern was obtained. We hypothesize that such approach will enhance classification efficacy of the BCI system.
OM&P
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Section BRAIN-COMPUTER INTERFACES, COGNITIVE NAVIGATION WORKSHOP AND NEUROENGINEERING
Acknowledgements
The research was supported by the Russian Science Foundation (grant 15-19-20053). References
1. Connell, L. A., Lincoln, N. B., and Radford, K. A. (2008). Somatosensory impairment after stroke: frequency of different deficits and their recovery. Clin. Rehabil. 22, 758-767.
2. Cifu, D. X., and Stewart, D. G. (1999). Factors affecting functional outcome after stroke: a critical review of rehabilitation interventions. Arch. Phys. Med. Rehabil. 80, S35-S39
3. Go, A. S., Mozaffarian, D., Roger, V. L., Benjamin, E. J., Berry, J. D., Blaha, M. J., et al. (2014). Heart disease and stroke statistics - 2014 update: a report from the American heart association. Circulation 129, e28-e292.
4. Ifft P. J. et al. A brain-machine interface enables bimanual arm movements in monkeys //Science translation-al medicine. - 2013. - T. 5. - №. 210. - C. 1-13.
