Dataset Information

Predicting Individualized Joint Kinematics Over Continuous Variations of Walking, Running, and Stair Climbing.

ABSTRACT: Goal: Accounting for gait individuality is important to positive outcomes with wearable robots, but manually tuning multi-activity models is time-consuming and not viable in a clinic. Generalizations can possibly be made to predict gait individuality in unobserved conditions. Methods: Kinematic individuality-how one person's joint angles differ from the group-is quantified for every subject, joint, ambulation mode (walking, running, stair ascent, and stair descent), and intramodal task (speed, incline) in an open-access dataset with 10 able-bodied subjects. Four N-way ANOVAs test how prediction methods affect the fit to experimental data between and within ambulation modes. We test whether walking individuality (measured at a single speed on level ground) carries across modes, or whether a mode-specific prediction (based on a single task for each mode) is significantly more effective. Results: Kinematic individualization improves fit across joint and task if we consider each mode separately. Across all modes, tasks, and joints, modal individualization improved the fit in 81% of trials, improving the fit on average by 4.3[Formula: see text] across the gait cycle. This was statistically significant at all joints for walking and running, and half the joints for stair ascent/descent. Conclusions: For walking and running, kinematic individuality can be easily generalized within mode, but the trends are mixed on stairs depending on joint.

SUBMITTER: Reznick E

PROVIDER: S-EPMC9928215 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Predicting Individualized Joint Kinematics Over Continuous Variations of Walking, Running, and Stair Climbing.

Reznick Emma E Welker Cara Gonzalez CG Gregg Robert D RD

IEEE open journal of engineering in medicine and biology 20220101

<i>Goal:</i> Accounting for gait individuality is important to positive outcomes with wearable robots, but manually tuning multi-activity models is time-consuming and not viable in a clinic. Generalizations can possibly be made to predict gait individuality in unobserved conditions. <i>Methods:</i> Kinematic individuality-how one person's joint angles differ from the group-is quantified for every subject, joint, ambulation mode (walking, running, stair ascent, and stair descent), and intramodal ...[more]

PMID: 36819935

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Project description:BackgroundJoint Hypermobility Syndrome (JHS) presents with a range of symptoms including widespread joint hypermobility and chronic arthralgia. The study objective was to investigate whether impairments in JHS are due to hypermobility or another factor of JHS by identifying impairments in gait and stair-climbing tasks; an activity that is demanding and so may better show differences between the cohorts.MethodsSixty-eight adults participated; 23 JHS, 23 Generalised Joint Hypermobility (GJH), and 22 Normal Flexibility (NF). Inclusion criteria for JHS participants were a positive classification using the Brighton Criteria, for GJH a Beighton Score ≥ 4, and for NF a Beighton Score < 4 with no hypermobile knees. Participants were recorded with a 10-camera Vicon system whilst they performed gait and stair-climbing. Temporal-spatial, and sagittal plane kinematic and kinetic outcome measures were calculated and input to statistical analyses by statistical parametric mapping (SPM).ResultsDuring the gait activity JHS had significantly greater stride time and significantly lower velocity than NF, and significantly greater stride time, lower velocity, and lower stride length than GJH. SPM analysis showed no significant differences between groups in gait kinematics. There were significant differences between groups for gait moments and powers; people with JHS tended to have lower moments and generate less power at the ankle, and favour power generation at the knee. A similar strategy was present in stair ascent. During stair descent people with JHS showed significantly more hip flexion than people with NF.ConclusionsAs there was only one significant difference between GJH and NF we conclude that impairments cannot be attributed to hypermobility alone, but rather other factor(s) of JHS. The results show that both gait and stair-climbing is impaired in JHS. Stair-climbing results indicate that JHS are using a knee-strategy and avoiding use of the ankle, which may be a factor for clinicians to consider during treatment.

Dataset Information

Predicting Individualized Joint Kinematics Over Continuous Variations of Walking, Running, and Stair Climbing.

Publications

Predicting Individualized Joint Kinematics Over Continuous Variations of Walking, Running, and Stair Climbing.

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