Friction and gravity represent two basic physical constraints of terrestrial locomotion that affect both motor patterns and the biomechanics of bipedal gait. To provide insights into the spatiotemporal organization of the motor output in connection with ground contact forces, we studied adaptation of human gait to steady low-friction conditions. Subjects walked along a slippery walkway (7 m long; friction coefficient ≃ 0.06) or a normal, nonslippery floor at a natural speed. We recorded gait kinematics, ground reaction forces, and bilateral electromyographic (EMG) activity of 16 leg and trunk muscles and we mapped the recorded EMG patterns onto the spinal cord in approximate rostrocaudal locations of the motoneuron (MN) pools to characterize the spatiotemporal organization of the motor output. The results revealed several idiosyncratic features of walking on the slippery surface. The step length, cycle duration, and horizontal shear forces were significantly smaller, the head orientation tended to be stabilized in space, whereas arm movements, trunk rotations, and lateral trunk inclinations considerably increased and foot motion and gait kinematics resembled those of a nonplantigrade gait. Furthermore, walking on the slippery surface required stabilization of the hip and of the center-of-body mass in the frontal plane, which significantly improved with practice. Motor patterns were characterized by an enhanced (roughly twofold) level of MN activity, substantial decoupling of anatomical synergists, and the absence of systematic displacements of the center of MN activity in the lumbosacral enlargement. Overall, the results show that when subjects are confronted with unsteady surface conditions, like the slippery floor, they adopt a gait mode that tends to keep the COM centered over the supporting limbs and to increase limb stiffness. We suggest that this behavior may represent a distinct gait mode that is particularly suited to uncertain surface conditions in general.
A numerical frame work of magnetically driven Powell-Eyring nanofluid using single phase model
