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CORRECTION article

Front. Neurosci., 25 January 2016
Sec. Neural Technology
Volume 9 - 2015 | https://doi.org/10.3389/fnins.2015.00517
This article is part of the Research Topic Augmentation of Brain Function: Facts, Fiction and Controversy View all 150 articles

Corrigendum: A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings

\r\nElizaveta OkorokovaElizaveta Okorokova1Mikhail LebedevMikhail Lebedev2Michael LindermannMichael Lindermann3Alex Ossadtchi,*Alex Ossadtchi1,4*
  • 1Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia
  • 2Department of Neurobiology, Duke University, Durham, NC, USA
  • 3Department of Biomedical Engineering, Norconnect Inc., Ogdensburg, NY, USA
  • 4Laboratory of Control of Complex Systems, Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, St. Petersburg, Russia

A corrigendum on
A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings

by Okorokova, E., Lebedev, M., Linderman, M., and Ossadtchi, A. (2015). Front. Neurosci. 9:389. doi: 10.3389/fnins.2015.00389

The correct acknowledgment should read:

The authors are grateful for the fruitful comments of Dr. Igor Furtat related to the algorithmic portion of the work. The experimental portion (Section 3) was prepared within the framework of a subsidy granted to the National Research University Higher School of Economics by the Government of the Russian Federation for the implementation of the Global Competitiveness Program. The data fusion algorithm for reconstruction of pen traces (Section 2) was adapted to the use with the EMG data solely under support of RNF (grant 14-29-00142) in IPME RAS.

The change requested does not affect the scientific validity of the results.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Keywords: handwriting, electromyography, pattern recognition, dynamical modeling, the Kalman filter, the Wiener filter

Citation: Okorokova E, Lebedev M, Lindermann M and Ossadtchi A (2016) Corrigendum: A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings. Front. Neurosci. 9:517. doi: 10.3389/fnins.2015.00517

Received: 20 December 2015; Accepted: 22 December 2015;
Published: 25 January 2016.

Edited and reviewed by: Giovanni Mirabella, Sapienza University, Italy

Copyright © 2016 Okorokova, Lebedev, Lindermann and Ossadtchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Alex Ossadtchi, ossadtchi@gmail.com

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