CORRECTION article

Front. Robot. AI, 20 November 2018

Sec. Biomedical Robotics

Volume 5 - 2018 | https://doi.org/10.3389/frobt.2018.00127

Corrigendum: Benchmark Datasets for Bilateral Lower-Limb Neuromechanical Signals from Wearable Sensors during Unassisted Locomotion in Able-Bodied Individuals

  • 1. Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, United States

  • 2. Department of Biomedical Engineering, Northwestern University, Evanston, IL, United States

  • 3. Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States

  • 4. Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States

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In the original article, there were two errors. In the text, the abbreviation for semitendinosus was omitted. In the text, the URL to the data repository available on Figshare was also incorrect.

Corrections have been made to Materials and Methods, Sub-section Instrumentation Setup, Paragraph one and Results, Paragraph one.

EMG signals were recorded using bipolar surface electrodes (DE2.1; Delsys, Boston, MA, USA) from the same seven muscles in each leg: tibialis anterior (TA), medial gastrocnemius (MG), soleus (SOL), vastus lateralis (VL), rectus femoris (RF), biceps femoris (BF), and semitendinosus (ST).

The data are saved in CSV format in subject-specific folders and are available to download from Figshare at https://doi.org/10.6084/m9.figshare.5362627.

The authors apologize for these errors and state that they do not change the scientific conclusions of the article in any way. The original article has been updated.

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Conflict of interest

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.

Summary

Keywords

gait, locomotion, biomechanics, electromyography, benchmark

Citation

Hu B, Rouse E and Hargrove L (2018) Corrigendum: Benchmark Datasets for Bilateral Lower-Limb Neuromechanical Signals from Wearable Sensors during Unassisted Locomotion in Able-Bodied Individuals. Front. Robot. AI 5:127. doi: 10.3389/frobt.2018.00127

Received

12 September 2018

Accepted

26 October 2018

Published

20 November 2018

Volume

5 - 2018

Edited and reviewed by

Diego Torricelli, Consejo Superior de Investigaciones Científicas (CSIC), Spain

Updates

Copyright

*Correspondence: Blair Hu

This article was submitted to Biomedical Robotics, a section of the journal Frontiers in Robotics and AI

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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