Dataset Information

Comparison of lower extremity joint mechanics between healthy active young and middle age people in walking and running gait.

ABSTRACT: Progression of age can influence gait characteristics. Previous research has investigated lower extremity joint mechanics between young and elderly people in locomotion, however little is known about whether differences exist between young and middle age people. Ten young healthy subjects (22.8?±?5.3 years) and ten middle age healthy subjects (50.7?±?6.0 years) engaged in treadmill walking (from 0.8 to 2.0?m/s) and running (from 1.8 to 3.8?m/s). The middle age group had higher ankle plantar flexor moment angular impulse (p?=?0.002), total support moment impulse (p?=?0.016), and hip stance positive work (p?=?0.029) across walking speeds. Additionally, the middle age group had higher knee flexion angle at ground contact in walking (p?=?0.005) and running (p?=?0.037). These findings indicate that moderate age affects changes in ankle and hip kinetic characteristics in walking, and knee kinematic patterns in both walking and running.

SUBMITTER: Jin L

PROVIDER: S-EPMC6447628 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Comparison of lower extremity joint mechanics between healthy active young and middle age people in walking and running gait.

Jin Li L Hahn Michael E ME

Scientific reports 20190403 1

Progression of age can influence gait characteristics. Previous research has investigated lower extremity joint mechanics between young and elderly people in locomotion, however little is known about whether differences exist between young and middle age people. Ten young healthy subjects (22.8 ± 5.3 years) and ten middle age healthy subjects (50.7 ± 6.0 years) engaged in treadmill walking (from 0.8 to 2.0 m/s) and running (from 1.8 to 3.8 m/s). The middle age group had higher ankle plantar flex ...[more]

PMID: 30944360

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Project description:Lower-limb wearable robotic devices can improve clinical gait and reduce energetic demand in healthy populations. To help enable real-world use, we sought to examine how assistance should be applied in variable gait conditions and suggest an approach derived from knowledge of human locomotion mechanics to establish a 'roadmap' for wearable robot design. We characterized the changes in joint mechanics during walking and running across a range of incline/decline grades and then provide an analysis that informs the development of lower-limb exoskeletons capable of operating across a range of mechanical demands. We hypothesized that the distribution of limb-joint positive mechanical power would shift to the hip for incline walking and running and that the distribution of limb-joint negative mechanical power would shift to the knee for decline walking and running. Eight subjects (6M,2F) completed five walking (1.25 m s-1) trials at -8.53°, -5.71°, 0°, 5.71°, and 8.53° grade and five running (2.25 m s-1) trials at -5.71°, -2.86°, 0°, 2.86°, and 5.71° grade on a treadmill. We calculated time-varying joint moment and power output for the ankle, knee, and hip. For each gait, we examined how individual limb-joints contributed to total limb positive, negative and net power across grades. For both walking and running, changes in grade caused a redistribution of joint mechanical power generation and absorption. From level to incline walking, the ankle's contribution to limb positive power decreased from 44% on the level to 28% at 8.53° uphill grade (p < 0.0001) while the hip's contribution increased from 27% to 52% (p < 0.0001). In running, regardless of the surface gradient, the ankle was consistently the dominant source of lower-limb positive mechanical power (47-55%). In the context of our results, we outline three distinct use-modes that could be emphasized in future lower-limb exoskeleton designs 1) Energy injection: adding positive work into the gait cycle, 2) Energy extraction: removing negative work from the gait cycle, and 3) Energy transfer: extracting energy in one gait phase and then injecting it in another phase (i.e., regenerative braking).

Project description:We present a real time algorithm for humanoid 3D walking and/or running based on a Model Predictive Control (MPC) approach. The objective is to generate a stable gait that replicates a footstep plan as closely as possible, that is, a sequence of candidate footstep positions and orientations with associated timings. For each footstep, the plan also specifies an associated reference height for the Center of Mass (CoM) and whether the robot should reach the footstep by walking or running. The scheme makes use of the Variable-Height Inverted Pendulum (VH-IP) as a prediction model, generating in real time both a CoM trajectory and adapted footsteps. The VH-IP model relates the position of the CoM to that of the Zero Moment Point (ZMP); to avoid falling, the ZMP must be inside a properly defined support region (a 3D extension of the 2D support polygon) whenever the robot is in contact with the ground. The nonlinearity of the VH-IP is handled by splitting the gait generation into two consecutive stages, both requiring to solve a quadratic program. Thanks to a particular triangular structure of the VH-IP dynamics, the first stage deals with the vertical dynamics using the Ground Reaction Force (GRF) as a decision variable. Using the prediction given by the first stage, the horizontal dynamics become linear time-varying. During the flight phases, the VH-IP collapses to a free-falling mass model. The proposed formulation incorporates constraints in order to maintain physically meaningful values of the GRF, keep the ZMP in the support region during contact phases, and ensure that the adapted footsteps are kinematically realizable. Most importantly, a stability constraint is enforced on the time-varying horizontal dynamics to guarantee a bounded evolution of the CoM with respect to the ZMP. Furthermore, we show how to extend the technique in order to perform running on tilted surfaces. We also describe a simple technique that receives input high-level velocity commands and generates a footstep plan in the form required by the proposed MPC scheme. The algorithm is validated via dynamic simulations on the full-scale humanoid robot HRP-4, as well as experiments on the small-sized robot OP3.

Dataset Information

Comparison of lower extremity joint mechanics between healthy active young and middle age people in walking and running gait.

Publications

Comparison of lower extremity joint mechanics between healthy active young and middle age people in walking and running gait.

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