Human walking along a curved path. II. Gait features and EMG patterns

Grégoire Courtine, Marco Schieppati

Research output: Contribution to journalArticlepeer-review


We recorded basic gait features and associated patterns of leg muscle activity, occurring during continuous body progression when humans walked along a curved trajectory, in order to gain insight into the nervous mechanisms underlying the control of the asymmetric movements of the two legs. The same rhythm was propagated to both legs, in spite of inner and outer strides diverging in length(P <0.001). There was a phase lag in limb displacement between the inner and outer leg of 7% of the total cycle duration (P = 0.0001). Swing velocity was greater for outer than inner foot (P <0.001). The duration of the stance phase diminished and increased in the outer and inner leg (P <0.01), respectively, and was associated with trunk leaning toward the inside of the path. Muscle activity was not dramatically altered during curved walking. The amplitude of soleus burst during stance increased in the outer (P <0.05) and decreased in the inner leg (P <0.05), without changes in timing. Tibialis anterior activity increased in both legs during the swing phase (P <0.05); it was advanced on the outer and delayed on the inner side (P <0.01; 2% of the cycle). The peroneus longus burst decreased in both legs, but more in the inner than the outer leg, and lasted longer in the inner leg at the onset of swing. Closing the eyes did not affect the gait pattern and muscle activity during turning. The command to walk along a curved path may exploit the basic mechanisms of the spinal locomotor generator, thereby limiting the computational cost of turning.

Original languageEnglish
Pages (from-to)191-205
Number of pages15
JournalEuropean Journal of Neuroscience
Issue number1
Publication statusPublished - Jul 2003

ASJC Scopus subject areas

  • Neuroscience(all)


Dive into the research topics of 'Human walking along a curved path. II. Gait features and EMG patterns'. Together they form a unique fingerprint.

Cite this