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Construction of Gait Adaptation Model in Human Splitbelt Treadmill Walking
Author(s) -
Yuji Otoda,
Hiroshi Kimura,
Kunikatsu Takase
Publication year - 2009
Publication title -
applied bionics and biomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.397
H-Index - 23
eISSN - 1754-2103
pISSN - 1176-2322
DOI - 10.1155/2009/305061
Subject(s) - treadmill , kinematics , physical medicine and rehabilitation , gait , biomechanics , sitting , gait analysis , computer science , simulation , psychology , physical therapy , medicine , anatomy , physics , classical mechanics , pathology
There are a huge number of studies that measure kinematics, dynamics, the oxygen uptake and so on in human walking on the treadmill. Especially in walking on the splitbelt treadmill where the speed of the right and left belt is different, remarkable differences in kinematics are seen between normal and cerebellar disease subjects. In order to construct the gait adaptation model of such human splitbelt treadmill walking, we proposed a simple control model and made a newly developed 2D biped robot walk on the splitbelt treadmill. We combined the conventional limit-cycle based control consisting of joint PD-control, cyclic motion trajectory planning and a stepping reflex with a newly proposed adjustment of P-gain at the hip joint of the stance leg. We showed that the data of robot (normal subject model and cerebellum disease subject model) experiments had high similarities with the data of normal subjects and cerebellum disease subjects experiments carried out by Reisman et al. (2005) and Morton and Bastian (2006) in ratios and patterns. We also showed that P-gain at the hip joint of the stance leg was the control parameter of adaptation for symmetric gaits in splitbelt walking and P-gain adjustment corresponded to muscle stiffness adjustment by the cerebellum. Consequently, we successfully proposed the gait adaptation model in human splitbelt treadmill walking and confirmed the validity of our hypotheses and the proposed model using the biped robot.

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