Journal: bioRxiv

Article Title: Connecting the legs with a spring improves human running economy

doi: 10.1101/474650

Figure Lengend Snippet: Comparisons of average, absolute joint moments and powers across stance and swing for the four participants from Experiment 3. We compared moments and powers produced during natural running (dark red) to those produced during exotendon running. Average kinetics during exotendon runs were separated into the exotendon contribution (blue) and the biological contribution (light red). We report the p-values resulting from two-tailed paired t-tests comparing biological contributions to kinetics in natural and exotendon running below the axes (light red text) and comparing total kinetics in natural and exotendon runs above the bars (light blue). Asterisks indicate comparisons that were significant after Holm-Šidák corrections (alpha = 0.05). When running with the exotendon, during swing, hip, knee and ankle biological moments are reduced compared to natural running, as is knee power. During stance, hip and knee biological moments are reduced, along with knee and ankle powers. These reductions in biological moments suggest savings are achieved in both swing and stance. Total moments at the hip and knee, as well as total knee power, increased, demonstrating that adopting these kinematics without an exotendon would require additional effort compared to natural running.

Article Snippet: After low-pass filtering the marker positions at 15 Hz (4th order, zero-phase shift Butterworth), we computed joint angles using the OpenSim inverse kinematics tool.

Techniques: Produced, Two Tailed Test

Journal: BioMedical Engineering OnLine

Article Title: Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations

doi: 10.1186/s12938-016-0291-x

Figure Lengend Snippet: Representations of the used upper limb model with reference poses and markers. a Screenshot taken from OpenSim while displaying the used full arm model. The reference configuration is shown as a shaded overlay on an actual example configuration determined by the joint angle vector [ \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{elv}}$$\end{document} θ elv = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0^\circ $$\end{document} 0 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{sh\_elv}}$$\end{document} θ sh _ elv = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$63^\circ $$\end{document} 63 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{sh\_rot}}$$\end{document} θ sh _ rot = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$15^\circ $$\end{document} 15 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{el\_flex}}$$\end{document} θ el _ flex = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$95^\circ $$\end{document} 95 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{pro\_sup}}$$\end{document} θ pro _ sup = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$-60^\circ $$\end{document} - 60 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{dev\_c}}$$\end{document} θ dev _ c = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0^\circ $$\end{document} 0 ∘ , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta _\mathtt{{flex\_c}}$$\end{document} θ flex _ c = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$20^\circ $$\end{document} 20 ∘ ]. b Representation of the model’s exported structure in MATLAB producing the same actual configuration as in sub-figure ( a ) using the developed forward kinematics function (functionally equivalent to OpenSim’s version). c Locations of prototype markers that are solely used to the reconstruction of model-defined anatomical joint angles with the proposed algorithm. d Locations of virtual markers that are used for the algorithm validation process by serving as inputs to OpenSim’s inverse kinematics tool directly

Article Snippet: Although the computational demand of wrist angle calculations is higher than of the shoulder and the elbow, the algorithm has still higher overall time efficiency than the optimization approach used by OpenSim’s inverse kinematics tool, as it is shown in the " " section.

Techniques: Plasmid Preparation, Biomarker Discovery

Journal: BioMedical Engineering OnLine

Article Title: Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations

doi: 10.1186/s12938-016-0291-x

Figure Lengend Snippet: Representative simulated movement pattern used for algorithm validation. Simulated movement patterns were generated to validate the proposed kinematic algorithm. 100 separate pseudo-random joint coordinate trajectories were constructed as 5th order Bézier-curves having 5 s duration and 100 Hz sampling frequency. PMx and VMx marker trajectories were calculated with our forward kinematics MATLAB function to generate simulated “measurement” data for the proposed algorithm and OpenSim

Article Snippet: Although the computational demand of wrist angle calculations is higher than of the shoulder and the elbow, the algorithm has still higher overall time efficiency than the optimization approach used by OpenSim’s inverse kinematics tool, as it is shown in the " " section.

Techniques: Biomarker Discovery, Generated, Construct, Sampling, Marker

Journal: Scientific Reports

Article Title: The impact of PCA derived gait kinematic variations on estimated medial knee contact forces in a knee osteoarthritis population

doi: 10.1038/s41598-025-90804-8

Figure Lengend Snippet: Functionally relevant changes (changes exceeding ± 10% BW) as result of kinematic variations in medial (MED) compartment knee contact forces and relative changes in lateral (LAT) compartment (relevant changes are depicted with filled red and blue circle) expressed as a % difference in body weight (BW) compared to knee contact forces estimated using the mean healthy gait pattern (black dotted lines), at the top. Solid grey lines are the cut-off/threshold for functionally relevant knee contact force changes (see Material and Methods section “ ”). Dotted grey lines define peak 1 (P1) and peak 2 (P2) of the gait cycle. Below (bottom) are the kinematics of the different joints contributing to the top 50% (see Fig. ) of the observed variation for each specific mode depicted as ± 1 STD (red, blue respectively). Grey dashed line defines the stance phase.

Article Snippet: Joint kinematics were calculated using the inverse kinematics tool in OpenSim Joint Articular Mechanics (JAM) using a validated musculoskeletal model with combined 12 degrees of freedom for the tibiofemoral (6DOF) and patellofemoral (6DOF) joints .

Techniques:

Journal: Scientific Reports

Article Title: The impact of PCA derived gait kinematic variations on estimated medial knee contact forces in a knee osteoarthritis population

doi: 10.1038/s41598-025-90804-8

Figure Lengend Snippet: Functionally relevant changes (changes exceeding ± 10% BW) as result of kinematic variations in medial (MED) compartment knee contact forces and relative changes in lateral (LAT) compartment (relevant changes are depicted with filled red and blue circle) expressed as a % difference in body weight (BW) compared to knee contact forces estimated using the mean knee OA gait pattern (black dotted lines), at the top. Solid grey lines are the cut-off/threshold for functionally relevant knee contact force changes (see Material and Methods section “ ”). Dotted grey lines define peak 1 (P1) and peak 2 (P2) of the gait cycle. Below (bottom) are the kinematics of the different joints contributing to the top 50% (see Fig. ) of the observed variation for each specific mode depicted as ± 1 STD (red, blue respectively). Grey dashed line defines the stance phase.

Article Snippet: Joint kinematics were calculated using the inverse kinematics tool in OpenSim Joint Articular Mechanics (JAM) using a validated musculoskeletal model with combined 12 degrees of freedom for the tibiofemoral (6DOF) and patellofemoral (6DOF) joints .

Techniques: