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Open AccessArticle

Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level

1
Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Universitetskaja Str., 1, 420500 Innopolis, Russia
2
Saratov State Medical University, Bolshaya Kazachya Str., 112, 410012 Saratov, Russia
3
Center for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, Pozuelo de Alarcón, 28223 Madrid, Spain
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2020, 20(8), 2362; https://doi.org/10.3390/s20082362
Received: 12 March 2020 / Revised: 18 April 2020 / Accepted: 20 April 2020 / Published: 21 April 2020
(This article belongs to the Special Issue Biennial State-of-the-Art Sensors Technology in Russia 2019-2020)
Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes. View Full-Text
Keywords: brain activity; functional near-infrared spectroscopy (fNIRS); real and imaginary motor execution; sensor level brain activity; functional near-infrared spectroscopy (fNIRS); real and imaginary motor execution; sensor level
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Hramov, A.E.; Grubov, V.; Badarin, A.; Maksimenko, V.A.; Pisarchik, A.N. Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level. Sensors 2020, 20, 2362.

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