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ObjectiveTo explore the reliability and validity of gait parameters obtained from gait assessment system software employing a human posture estimation algorithm based on markerless videos of children walking in clinical practice.MethodsEighteen typical developmental (TD) children and ten children with developmental dysplasia of the hip (DDH) were recruited to walk along a designated sidewalk at a comfortable walking speed. A 3-dimensional gait analysis (3D GA) and a 2-dimensional markerless (2D ML) gait evaluation system were used to extract the gait kinematics parameters twice at an interval of 2 h.ResultsThe two measurements of the children's kinematic gait parameters revealed no significant differences (P > 0.05). Intra-class correlation coefficients (ICC) were generally high (ICC >0.7), showing moderate to good relative reliability. The standard error of measurement (SEM) values of all gait parameters measured by the two walks were 1.26°–2.91°. The system software had good to excellent validity compared to the 3D GA, with ICC values between 0.835 and 0.957 and SEM values of 0.87°–1.71° for the gait parameters measured by both methods. The Bland–Altman plot analysis indicated no significant systematic errors.ConclusionsThe feasibility of the markerless gait assessment method using the human posture estimation-based algorithm may provide reliable and valid gait analysis results for practical clinical applications.

Purpose: Statistical shape methods have proven to be useful tools in providing statistical predications of several clinical and biomechanical features as to analyze and describe the possible link with them. In the present study, we aimed to explore and quantify the relationship between biometric features derived from imaging data and model-derived kinematics.Methods: Fifty-seven healthy males were gathered under strict exclusion criteria to ensure a sample representative of normal physiological conditions. MRI-based bone geometry was established and subject-specific musculoskeletal simulations in the Anybody Modeling System enabled us to derive personalized kinematics. Kinematic and shape findings were parameterized using principal component analysis. Partial least squares regression and canonical correlation analysis were then performed with the goal of predicting motion and exploring the possible association, respectively, with the given bone geometry. The relationship of hip flexion, abduction, and rotation, knee flexion, and ankle flexion with a subset of biometric features (age, length, and weight) was also investigated.Results: In the statistical kinematic models, mean accuracy errors ranged from 1.60° (race cycling) up to 3.10° (lunge). When imposing averaged kinematic waveforms, the reconstruction errors varied between 4.59° (step up) and 6.61° (lunge). A weak, yet clinical irrelevant, correlation between the modes describing bone geometry and kinematics was observed. Partial least square regression led to a minimal error reduction up to 0.42° compared to imposing gender-specific reference curves. The relationship between motion and the subject characteristics was even less pronounced with an error reduction up to 0.21°.Conclusion: The contribution of bone shape to model-derived joint kinematics appears to be relatively small and lack in clinical relevance.

Hemophilic arthropathy is the result of repetitive intra-articular bleeding and synovial inflammation. In people with hemophilic arthropathy (PWHA), very little is known about the neural control of individual muscles during movement. The aim of the present study was to assess if the neural control of individual muscles and coordination between antagonistic muscle pairs and joint kinematics during gait are affected in PWHA. Thirteen control subjects (CG) walked overground at their preferred and slow velocity (1 m/s), and 14 PWHA walked overground at the preferred velocity (1 m/s). Joint kinematics and temporal gait parameters were assessed using four inertial sensors. Surface electromyography (EMG) was collected from gluteus maximus (GMAX), gluteus medius (GMED), vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF), medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus (SOL), tibialis anterior (TA), semitendinosus (ST), and biceps femoris (BF). Waveforms were compared using the time-series analysis through statistical parametric mapping. In PWHA compared to CG, EMG amplitude during the stance phase was higher for LG (for both velocities of the CG), BF (slow velocity only), and ST (preferred velocity only) (p < 0.05). Co-contraction during the stance phase was higher for MG-TA, LG-TA, VL-BF, VM-ST, LG-VL, and MG-VM (both velocities) (p < 0.05). MG and LG were excited earlier (preferred velocity only) (p < 0.05). A later offset during the stance phase was found for VL, BF, and ST (both velocities), and BF and GMAX (preferred velocity only) (p < 0.05). In addition, the range of motion in knee and ankle joints was lower in PWHA (both velocities) and hip joint (preferred velocity only) (p < 0.05). In conclusion, the neural control of individual muscles and coordination between antagonistic muscles during gait in PWHA differs substantially from control subjects.

Hemophilic arthropathy is the result of repetitive intra-articular bleeding and synovial inflammation. In people with hemophilic arthropathy (PWHA), very little is known about the neural control of individual muscles during movement. The aim of the present study was to assess if the neural control of individual muscles and coordination between antagonistic muscle pairs and joint kinematics during gait are affected in PWHA. Thirteen control subjects (CG) walked overground at their preferred and slow velocity (1 m/s), and 14 PWHA walked overground at the preferred velocity (1 m/s). Joint kinematics and temporal gait parameters were assessed using four inertial sensors. Surface electromyography (EMG) was collected from gluteus maximus (GMAX), gluteus medius (GMED), vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF), medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus (SOL), tibialis anterior (TA), semitendinosus (ST), and biceps femoris (BF). Waveforms were compared using the time-series analysis through statistical parametric mapping. In PWHA compared to CG, EMG amplitude during the stance phase was higher for LG (for both velocities of the CG), BF (slow velocity only), and ST (preferred velocity only) (p < 0.05). Co-contraction during the stance phase was higher for MG-TA, LG-TA, VL-BF, VM-ST, LG-VL, and MG-VM (both velocities) (p < 0.05). MG and LG were excited earlier (preferred velocity only) (p < 0.05). A later offset during the stance phase was found for VL, BF, and ST (both velocities), and BF and GMAX (preferred velocity only) (p < 0.05). In addition, the range of motion in knee and ankle joints was lower in PWHA (both velocities) and hip joint (preferred velocity only) (p < 0.05). In conclusion, the neural control of individual muscles and coordination between antagonistic muscles during gait in PWHA differs substantially from control subjects. [ABSTRACT FROM AUTHOR]