The between-day repeatability, standard error of measurement and minimal detectable change for discrete kinematic parameters during treadmill running

Bramah, Christopher; Preece, Stephen; Gill, Niamh; Herrington, Lee

doi:10.1016/j.gaitpost.2020.12.032

Cited by 21 publications

(24 citation statements)

References 35 publications

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“…The former was indeed the case for at least one participant, whose markerless joint angles were considerably different between the MoCap and Sport clothing conditions, and were confirmed from raw video data to have visibly greater ranges of motion in hip, knee, and ankle flexion for the Sport clothing condition (Supplementary Material, Figure H). The RMSD values between clothing conditions, which could be considered analogous to a participant returning on a second day in different clothing, were smaller than published MDC values at initial contact (Bramah et al, 2021), with the exception of hip flexion (0.2° greater). These findings are consistent with a running repeatability study over three repeated visits at varying running speeds using the same markerless motion capture software (Moran et al, 2023).…”

Section: Discussioncontrasting

confidence: 62%

“…The RMSD values between clothing conditions, which could be considered analogous to a participant returning on a second day in different clothing, were smaller than published MDC values at initial contact 13 , with the exception of hip flexion (0.2° greater). These findings are consistent with a running repeatability study over three repeated visits at varying running speeds using the same markerless motion capture software 14 .…”

Section: Discussioncontrasting

confidence: 61%

“…Sagittal plane joint angles between motion capture systems had mean RMSD of 5.2° or less for all three joints, consistent with the findings of Tang et al 6 . The differences between systems measured as mean RMSD over the entire gait cycle are comparable to reported minimal detectable change (MDC) values for marker-based motion capture of treadmill running at initial contact 13 . Compared to the marker-based MDC values, the RMSD values between systems are 3.1° smaller (for ankle dorsiflexion) to 4.7° greater (for knee ab/adduction).…”

Section: Discussionsupporting

confidence: 56%

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Comparison of concurrent and asynchronous running kinematics and kinetics from marker-based motion capture and markerless motion capture under two clothing conditions

Kanko

Outerleys

Laende

et al. 2023

Preprint

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Running gait analysis has been pursued as a potential tool to record and quantify athletes' movement patterns to predict injury, inform interventions, or improve performance. Limitations associated with marker-based motion capture have reduced its impact and applications. Markerless motion capture promises fewer limitations, but examining the relationship between markerless and marker-based motion capture data is important to understand how markerless results can be interpreted alongside historical data collected using marker-based motion capture. Further, markerless motion capture uses automated estimation of landmarks, which may be influenced by clothing. To investigate these aspects of markerless motion capture, we compared lower limb kinematic and kinetic measures during treadmill running from concurrent marker-based and markerless motion capture (Theia3D), and asynchronous markerless motion capture under realistic clothing conditions. Thirty healthy adults ran at a self-selected speed on an instrumented treadmill while concurrent marker-based and markerless motion capture data were recorded. The procedure was repeated with participants wearing athletic clothing while markerless data were recorded. Kinematic and kinetic measurements were consistent between markerless clothing conditions, indicating that the markerless system is robust to clothing, allowing data collection of participants in their preferred attire. Joint center positions between concurrent marker-based and markerless data differed by 3 cm or less. Sagittal plane joint angles differed by 5° or less between systems, while frontal and transverse plane joint angles differed by 5-10°. Similar joint moment patterns were captured except ankle inversion/eversion, and some moments differed in peak magnitudes. Differences between the marker-based and markerless systems were sensitive to coordinate system definitions, highlighting the importance of considering the effects of segment coordinate system definition when comparing against historical data or data from other motion capture modalities.

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Section: Discussioncontrasting

confidence: 62%

Section: Discussioncontrasting

confidence: 61%

Section: Discussionsupporting

confidence: 56%

See 1 more Smart Citation

Comparison of concurrent and asynchronous running kinematics and kinetics from marker-based motion capture and markerless motion capture under two clothing conditions

Kanko

Outerleys

Laende

et al. 2023

Preprint

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“…Where an individual changes by more than MDC, this would represent a real change. Recently, Riazati et al ( 2020 ) and Bramah et al ( 2021 ) used this approach with the former reporting different findings when using NHST and MDC approaches.…”

Section: Introductionmentioning

confidence: 99%

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

Riazati

Caplan²,

Matabuena³

et al. 2022

Front. Sports Act. Living

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PurposeTo 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.MethodsTwenty (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.ResultsImmediately 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.ConclusionHigh 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.

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“…The RMSE at peak joint angles between both DeepLabCut and OpenPose and the marker‐based approach are generally, however, larger than the minimum detectable change reported for peak joint angles from marker‐based motion capture (Figure 2; Figure 3), which are typically <5 degrees at speeds ranging from 2.5–3.4 m s −1 39–42 . In contrast, the minimum detectable change for joint excursions of the hip, knee, and ankle ranges from 4.5–8.3, 4.3–6.0, and 9.8–7.5 degrees, respectively, 40,42 and is more in line with the mean RMSE values reported over the whole gait cycle for temporally aligned and offset corrected DeepLabCut and OpenPose values.…”

Section: Discussionmentioning

confidence: 79%

The accuracy of markerless motion capture combined with computer vision techniques for measuring running kinematics

Hooren

Pecasse

Meijer

et al. 2023

Scandinavian Med Sci Sports

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Background Markerless motion capture based on low‐cost 2‐D video analysis in combination with computer vision techniques has the potential to provide accurate analysis of running technique in both a research and clinical setting. However, the accuracy of markerless motion capture for assessing running kinematics compared to a gold‐standard approach remains largely unexplored. Objective Here, we investigate the accuracy of custom‐trained (DeepLabCut) and existing (OpenPose) computer vision techniques for assessing sagittal‐plane hip, knee, and ankle running kinematics at speeds of 2.78 and 3.33 m s−1 as compared to gold‐standard marker‐based motion capture. Methods Differences between the markerless and marker‐based approaches were assessed using statistical parameter mapping and expressed as root mean squared errors (RMSEs). Results After temporal alignment and offset removal, both DeepLabCut and OpenPose showed no significant differences with the marker‐based approach at 2.78 m s−1, but some significant differences remained at 3.33 m s−1. At 2.78 m s−1, RMSEs were 5.07, 7.91, and 5.60, and 5.92, 7.81, and 5.66 degrees for the hip, knee, and ankle for DeepLabCut and OpenPose, respectively. At 3.33 m s−1, RMSEs were 7.40, 10.9, 8.01, and 4.95, 7.45, and 5.76 for the hip, knee, and ankle for DeepLabCut and OpenPose, respectively. Conclusion The differences between OpenPose and the marker‐based method were in line with or smaller than reported between other kinematic analysis methods and marker‐based methods, while these differences were larger for DeepLabCut. Since the accuracy differed between individuals, OpenPose may be most useful to facilitate large‐scale in‐field data collection and investigation of group effects rather than individual‐level analyses.

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The between-day repeatability, standard error of measurement and minimal detectable change for discrete kinematic parameters during treadmill running

Cited by 21 publications

References 35 publications

Comparison of concurrent and asynchronous running kinematics and kinetics from marker-based motion capture and markerless motion capture under two clothing conditions

Comparison of concurrent and asynchronous running kinematics and kinetics from marker-based motion capture and markerless motion capture under two clothing conditions

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

The accuracy of markerless motion capture combined with computer vision techniques for measuring running kinematics

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