Corrigendum: Benchmark datasets for bilateral lower-limb neuromechanical signals from wearable sensors during unassisted locomotion in able-bodied individuals [Front. Robot. AI 5, 14 (2018)] doi: 10.3389/frobt.2018.00014

Blair Hu*, Elliott J Rouse, Levi Hargrove

*Corresponding author for this work

Research output: Contribution to journalComment/debatepeer-review

Abstract

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).

Original languageEnglish (US)
Article number127
JournalFrontiers in Robotics and AI
Volume5
Issue numberNOV
DOIs
StatePublished - Nov 1 2018

Keywords

  • Benchmark
  • Biomechanics
  • Electromyography
  • Gait
  • Locomotion

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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