Markerless motion capture: What clinician-scientists need to know right now

Ito, Naoaki; Sigurðsson, Haraldur B.; Seymore, Kayla D.; Arhos, Elanna K; Buchanan, Thomas S.; Snyder‐Mackler, Lynn; Silbernagel, Karin Grävare

doi:10.1016/j.jsampl.2022.100001

Cited by 14 publications

(16 citation statements)

References 6 publications

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“…Kanko et al (2021a) found comparable kinematics between the two systems during treadmill walking. Ito et al (2022) added that kinematics during squatting and forward hopping were also comparable in the sagittal plane, but not in frontal and transverse planes. The only kinetic study to date is by Tang et al (2022), which reported between-system differences in peak joint moments and powers during treadmill running.…”

Section: Introductionmentioning

confidence: 99%

“…However, the fidelity of markerless motion capture in quantifying 3D joint kinematics and kinetics has not been fully verified against standard marker-based techniques. To our knowledge, only three recent studies compared lower extremity 3D kinematics or kinetics from concurrent marker-based and markerless motion capture (Ito et al, 2022; Kanko et al, 2021a; Tang et al, 2022). Kanko et al (2021a) found comparable kinematics between the two systems during treadmill walking.…”

Section: Introductionmentioning

confidence: 99%

“…The only kinetic study to date is by Tang et al (2022), which reported between-system differences in peak joint moments and powers during treadmill running. These studies either only assessed kinematics (Ito et al, 2022; Kanko et al, 2021a) or a single movement (Kanko et al, 2021a; Tang et al, 2022). No study has compared lower extremity 3D kinematics and kinetics between marker-based and markerless systems across multiple daily living or exercise movements.…”

Section: Introductionmentioning

confidence: 99%

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Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements

Song

Hullfish

Silva

et al. 2023

Preprint

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Motion analysis is essential for assessing in-vivo human biomechanics. Marker-based motion capture is the standard to analyze human motion, but the inherent inaccuracy and practical challenges limit its utility in large-scale and real-world applications. Markerless motion capture has shown promise to overcome these practical barriers. However, its fidelity in quantifying joint kinematics and kinetics has not been verified across multiple common human movements. In this study, we concurrently captured marker-based and markerless motion data on 10 healthy subjects performing 8 daily living and exercise movements. We calculated the correlation (Rxy) and root-mean-square difference (RMSD) between markerless and marker-based estimates of ankle dorsi-plantarflexion, knee flexion, and three-dimensional hip kinematics (angles) and kinetics (moments) during each movement. Estimates from markerless motion capture matched closely with marker-based in ankle and knee joint angles (Rxy≥ 0.877, RMSD ≤ 5.9°) and moments (Rxy≥ 0.934, RMSD ≤ 2.66 % height × weight). High outcome comparability means the practical benefits of markerless motion capture can simplify experiments and facilitate large-scale analyses. Hip angles and moments demonstrated more differences between the two systems (RMSD: 6.7° – 15.9° and up to 7.15 % height × weight), especially during rapid movements such as running. Markerless motion capture appears to improve the accuracy of hip-related measures, yet more research is needed for validation. We encourage the biomechanics community to continue verifying, validating, and establishing best practices for markerless motion capture, which holds exciting potential to advance collaborative biomechanical research and expand real-world assessments needed for clinical translation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Markerless motion capture estimates of lower extremity kinematics and kinetics are comparable to marker-based across 8 movements

Song

Hullfish

Silva

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…These approaches have recently experienced significant advances in flexibility and ease-ofuse, but achieving precise 3D trajectory tracking remains challenging. 15,35,36 Even in human studies, markerless techniques show only limited agreement with markerbased methods even under optimal conditions and typically generate mean errors of 10%. [21][22][23][24][25][35][36][37][38][39][40][41][42] .…”

Section: Introductionmentioning

confidence: 99%

“…15,35,36 Even in human studies, markerless techniques show only limited agreement with markerbased methods even under optimal conditions and typically generate mean errors of 10%. [21][22][23][24][25][35][36][37][38][39][40][41][42] . Importantly, further development of markerless techniques heavily depends on comparison with marker-based data 22,36,41 which serves as the ground truth in most advanced human studies.…”

Section: Introductionmentioning

confidence: 99%

Stimulatory effect of monoacylglycerol lipase inhibitor MJN110 on locomotion and step kinematics demonstrated by high-precision 3D motion capture in mice

Ignatowska‐Jankowska

Özer

Kuck

et al. 2023

Preprint

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The neuromodulatory endocannabinoid system is a promising target for therapeutic interventions. One of well-known behavioral effects of cannabinoid CB1 receptor activation with exogenous ligands such as THC is the inhibition of locomotor activity. However, the behavioral effects of endogenous cannabinoids have not been extensively studied. Despite broad medicinal and recreational use of cannabinoids, little is known about their effects on fine movements, critical for therapeutic applications. Such fine motor function is only resolvable with the precision of marker-based motion capture, which so far has not been available in freely moving mice. Therefore, we have adapted a high-speed, high-resolution marker-based 3D motion capture system to track movement (3D trajectories and speed of markers) during voluntary locomotor tasks in mice. Here we show that enhancing endocannabinoid signaling produces bidirectional effects on locomotor behavior that differ from those caused by exogenous cannabinoid receptor agonist, in unrestricted mice. Given our expectation of subtle rather than dramatic changes with the low and potentially therapeutic doses, we employed a sensitive and accurate marker-based 3D motion capture system to resolve the finest differences in full-body kinematic signatures of mice exploring horizontal and vertical environments. We found that selective upregulation of either of the two main endocannabinoids 2-arachidonoylglycerol (2-AG) or anandamide (AEA) with selective inhibitors of their degradation (MJN110 and PF3845, respectively), produced opposite effects: PF3845 suppressed locomotor activity whereas MJN110 enhanced it. Furthermore, while low doses of the synthetic cannabinoid agonist CP55,940 decreased locomotion in a an open field exploration task as expected, it surprisingly did not affect performance in a vertical climbing task. The results show that the effects of cannabinoid signaling on behavior are not predominantly inhibitory as commonly assumed. Furthermore, we found that the invariant microstructure of locomotory behavior remains unchanged under all treatments, pointing towards motivational rather than motor-related mechanisms of action.

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