Absolute Reliability of Gait Parameters Acquired With Markerless Motion Capture in Living Domains.

Purpose: To examine the between-day absolute reliability of gait parameters acquired with Theia3D markerless motion capture for use in biomechanical and clinical settings. Methods: Twenty-one (7 M,14 F) participants aged between 18 and 73 years were recruited in community locations to perform two walking tasks: self-selected and fastest-comfortable walking speed. Participants walked along a designated walkway on two separate days.Joint angle kinematics for the hip, knee, and ankle, for all planes of motion, and spatiotemporal parameters were extracted to determine absolute reliability between-days. For kinematics, absolute reliability was examined using: full curve analysis [root mean square difference (RMSD)] and discrete point analysis at defined gait events using standard error of measurement (SEM). The absolute reliability of spatiotemporal parameters was also examined using SEM and SEM%. Results: Markerless motion capture produced low measurement error for kinematic full curve analysis with RMSDs ranging between 0.96° and 3.71° across all joints and planes for both walking tasks. Similarly, discrete point analysis within the gait cycle produced SEM values ranging between 0.91° and 3.25° for both sagittal and frontal plane angles of the hip, knee, and ankle. The highest measurement errors were observed in the transverse plane, with SEM >5° for ankle and knee range of motion. For the majority of spatiotemporal parameters, markerless motion capture produced low SEM values and SEM% below 10%. Conclusion: Markerless motion capture using Theia3D offers reliable gait analysis suitable for biomechanical and clinical use.

Feasibility of Markerless Motion Capture for Three-Dimensional Gait Assessment in Community Settings.

Three-dimensional (3D) kinematic analysis of gait holds potential as a digital biomarker to identify neuropathologies, monitor disease progression, and provide a high-resolution outcome measure to monitor neurorehabilitation efficacy by characterizing the mechanisms underlying gait impairments. There is a need for 3D motion capture technologies accessible to community, clinical, and rehabilitation settings. Image-based markerless motion capture (MLMC) using neural network-based deep learning algorithms shows promise as an accessible technology in these settings. In this study, we assessed the feasibility of implementing 3D MLMC technology outside the traditional laboratory environment to evaluate its potential as a tool for outcomes assessment in neurorehabilitation. A sample population of 166 individuals aged 9-87 years (mean 43.7, S.D. 20.4) of varied health history were evaluated at six different locations in the community over a 3-month period. Participants walked overground at self-selected (SS) and fastest comfortable (FC) speeds. Feasibility measures considered the expansion, implementation, and practicality of this MLMC system. A subset of the sample population (46 individuals) walked over a pressure-sensitive walkway (PSW) concurrently with MLMC to assess agreement of the spatiotemporal gait parameters measured between the two systems. Twelve spatiotemporal parameters were compared using mean differences, Bland-Altman analysis, and intraclass correlation coefficients for agreement (ICC2,1) and consistency (ICC3,1). All measures showed good to excellent agreement between MLMC and the PSW system with cadence, speed, step length, step time, stride length, and stride time showing strong similarity. Furthermore, this information can inform the development of rehabilitation strategies targeting gait dysfunction. These first experiments provide evidence for feasibility of using MLMC in community and clinical practice environments to acquire robust 3D kinematic data from a diverse population. This foundational work enables future investigation with MLMC especially its use as a digital biomarker of disease progression and rehabilitation outcome.

Gait and Neuromuscular Changes Are Evident in Some Masters Club Level Runners 24-h After Interval Training Run.

Purpose: To examine the time course of recovery for gait and neuromuscular function immediately after and 24-h post interval training. In addition, this study compared the impact of different statistical approaches on detecting changes. Methods: Twenty (10F, 10M) healthy, recreational club runners performed a high-intensity interval training (HIIT) session consisting of six repetitions of 800 m. A 6-min medium intensity run was performed pre, post, and 24-h post HIIT to assess hip and knee kinematics and coordination variability. Voluntary activation and twitch force of the quadriceps, along with maximum isometric force were examined pre, post, and 24-h post significance HIIT. The time course of changes were examined using two different statistical approaches: traditional null hypothesis significance tests and "real" changes using minimum detectable change. Results: Immediately following the run, there were significant (P < 0.05) increases in the hip frontal kinematics and coordination variability. The runners also experienced a loss of muscular strength and neuromuscular function immediately post HIIT (P < 0.05). Individual assessment, however, showed that not all runners experienced fatigue effects immediately post HIIT. Null hypothesis significance testing revealed a lack of recovery in hip frontal kinematics, coordination variability, muscle strength, and neuromuscular function at 24-h post, however, the use of minimum detectable change suggested that most runners had recovered. Conclusion: High intensity interval training resulted in altered running kinematics along with central and peripheral decrements in neuromuscular function. Most runners had recovered within 24-h, although a minority still exhibited signs of fatigue. The runners that were not able to recover prior to their run at 24-h were identified to be at an increased risk of running-related injury.

Fatigue Induced Changes in Muscle Strength and Gait Following Two Different Intensity, Energy Expenditure Matched Runs.

PURPOSE: To investigate changes in hip and knee strength, kinematics, and running variability following two energy expenditure matched training runs; a medium intensity continuous run (MICR) and a high intensity interval training session (HIIT). METHODS: Twenty (10 Females, 10 Males) healthy master class runners were recruited. Each participant completed the HIIT consisting of six repetitions of 800 m with a 1:1 work: rest ratio. The MICR duration was set to match energy expenditure of the HIIT session. Hip and knee muscular strength were examined pre and post both HIIT and MICR. Kinematics and running variability for hip and knee, along with spatiotemporal parameters were assessed at start and end of each run-type. Changes in variables were examined using both 2 × 2 ANOVAs with repeated measures and on an individual level when the change in a variable exceeded the minimum detectable change (MDC). RESULTS: All strength measures exhibited significant reductions at the hip and knee (P < 0.05) with time for both run-types; 12% following HIIT, 10.6% post MICR. Hip frontal plane kinematics increased post run for both maximum angle (P < 0.001) and range of motion (P = 0.003). Runners exhibited increased running variability for nearly all variables, with the HIIT having a greater effect. Individual assessment revealed that not all runners were effected post run and that following HIIT more runners had reduced muscular strength, altered kinematics and increased running variability. CONCLUSION: Runners exhibited fatigue induced changes following typical training runs, which could potentially present risk of injury development. Group and individual assessment revealed different findings where the use of MDC is recommended over that of P-values.

Hypogravity reduces trunk admittance and lumbar muscle activation in response to external perturbations.

Reduced paraspinal muscle size and flattening of spinal curvatures have been documented after spaceflight. Assessment of trunk adaptations to hypogravity can contribute to development of specific countermeasures. In this study, parabolic flights were used to investigate spinal curvature and muscle responses to hypogravity. Data from five trials at 0.25 g, 0.50 g, and 0.75 g were recorded from six participants positioned in a kneeling-seated position. During the first two trials, participants maintained a normal, upright posture. In the last three trials, small-amplitude perturbations were delivered in the anterior direction at the T10 level. Spinal curvature was estimated with motion capture cameras. Trunk displacement and contact force between the actuator and participant were recorded. Muscle activity responses were collected by intramuscular electromyography (iEMG) of the deep and superficial lumbar multifidus, iliocostalis lumborum, longissimus thoracis, quadratus lumborum, transversus abdominis, obliquus internus, and obliquus externus muscles. The root mean square iEMG and the average spinal angles were calculated. Trunk admittance and muscle responses to perturbations were calculated as closed-loop frequency-response functions. Compared with 0.75 g, 0.25 g resulted in lower activation of the longissimus thoracis (P = 0.002); lower responses of the superficial multifidus at low frequencies (P = 0.043); lower responses of the superficial multifidus (P = 0.029) and iliocostalis lumborum (P = 0.043); lower trunk admittance (P = 0.037) at intermediate frequencies; and stronger responses of the transversus abdominis at higher frequencies (P = 0.032). These findings indicate that exposure to hypogravity reduces trunk admittance, partially compensated by weaker stabilizing contributions of the paraspinal muscles and coinciding with an apparent increase of deep abdominal muscle activity.NEW & NOTEWORTHY This study presents for the first time novel insights into the adaptations to hypogravity of spinal curvatures, trunk stiffness, and paraspinal muscle activity. We showed that exposure to hypogravity reduces the displacement of the trunk by an applied perturbation, partially compensated by weaker stabilizing contributions of the paraspinal muscles and concomitant increase in abdominal muscle responses. These findings may have relevance for future recommendations for planetary surface explorations.

The number of strides required for treadmill running gait analysis is unaffected by either speed or run duration.

Participation in running events has increased recently, with a concomitant increase in the rate of running related injuries (RRI). Mechanical overload is thought to be a primary cause of RRI, it is often detected using motion analysis to examine running mechanics during either overground or treadmill running. In treadmill running, no clear consensus for the number of strides required to establish stable kinematic data exists. The aim of this study was to establish the number of strides needed for stable data when analysing gait kinematics in the stance phase of treadmill running. Twenty healthy, masters age group, club runners completed a high intensity interval training run (HIIT) and an energy-expenditure matched medium intensity continuous run (MICR). Thirty consecutive strides at start and end of each run were identified. Sequential averaging was employed to determine the number of strides required to establish a stable value. No significant differences existed in the number of strides required to achieve stable values. Twenty consecutive strides are required to be 95% confident stable values exist for maximum angle, angle at initial foot contact, and range of motion at the ankle, knee, and hip joints variables at the ankle, knee, and hip joints, in all three planes of motion, and spatiotemporal regardless of running speed and time of capture.