4.5 Article

Lower limb biomechanical analysis during an unanticipated step on a bump reveals specific adaptations of walking on uneven terrains

Journal

JOURNAL OF EXPERIMENTAL BIOLOGY
Volume 220, Issue 22, Pages 4169-4176

Publisher

COMPANY OF BIOLOGISTS LTD
DOI: 10.1242/jeb.161158

Keywords

Electromyography; Preferred walking speed; Unanticipated bump; Irregular surface

Categories

Funding

  1. Defense Advanced Research Projects Agency (DARPA), WarriorWeb Program [W911NF-14-C-0051]
  2. Wyss Institute for Biologically Inspired Engineering
  3. Harvard John A. Paulson School of Engineering and Applied Sciences
  4. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo grant (FAPESP) [2015/02116-1]
  5. Samsung Scholarship
  6. Funai Overseas Scholarship
  7. National Science Foundation Graduate Research Fellowship [DGE1144152]

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Although it is clear that walking over different irregular terrain is associated with altered biomechanics, there is little understanding of how we quickly adapt to unexpected variations in terrain. This study aims to investigate which adaptive strategies humans adopt when performing an unanticipated step on an irregular surface, specifically a small bump. Nine healthy male participants walked at their preferred walking speed along a straight walkway during five conditions: four involving unanticipated bumps of two different heights, and one level walking condition. Muscle activation of eight lower limb muscles and three-dimensional gait analysis were evaluated during these testing conditions. Two distinct adaptive strategies were found, which involved no significant change in total lower limb mechanical work or walking speed. An ankle-based strategy was adopted when stepping on a bump with the forefoot, whereas a hip-based strategy was preferred when stepping with the rearfoot. These strategies were driven by a higher activation of the plantarflexor muscles (6-51%), which generated a higher ankle joint moment during the forefoot conditions and by a higher activation of the quadriceps muscles (36-93%), which produced a higher knee joint moment and hip joint power during the rearfoot conditions. These findings provide insights into how humans quickly react to unexpected events and could be used to inform the design of adaptive controllers for wearable robots intended for use in unstructured environments that can provide optimal assistance to the different lower limb joints.

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