Ground reaction forces and moments (GRFs and GRMs) measured from force plates in a gait laboratory are usually used as the input conditions to predict the knee joint forces and moments via musculoskeletal (MSK) multibody dynamics (MBD) model. However, the measurements of the GRFs and GRMs data rely on force plates and sometimes are limited by the difficulty in some patient's gait patterns (e.g. treadmill gait). In addition, the force plate calibration error may influence the prediction accuracy of the MSK model. In this study, a prediction method of the GRFs and GRMs based on elastic contact element was integrated into a subject-specific MSK MBD modelling framework of total knee arthroplasty (TKA), and the GRFs and GRMs and knee contact forces (KCFs) during walking were predicted simultaneously with reasonable accuracy. The ground reaction forces and moments were predicted with an average root mean square errors (RMSEs) of 0.021 body weight (BW), 0.014 BW and 0.089 BW in the antero-posterior, medio-lateral and vertical directions and 0.005 BW•body height (BH), 0.011 BW•BH, 0.004 BW•BH in the sagittal, frontal and transverse planes, respectively. Meanwhile, the medial, lateral and total tibiofemoral (TF) contact forces were predicted by the developed MSK model with RMSEs of 0.025-0.032 BW, 0.018-0.022 BW, and 0.089-0.132 BW, respectively. The accuracy of the predicted medial TF contact force was improved by 12% using the present method. The proposed method can extend the application of the MSK model of TKA and is valuable for understanding the in vivo knee biomechanics and tribological conditions without the force plate data.

Objective, Total talar replacement (TTR) using a customised talus prosthesis is an emerging surgical alternative to conventional total ankle arthroplasty (TAA) for treating ankle problems. Upon satisfying clinical reports in the literature, this study explored the advantages of TTR in restoring foot biomechanics during walking compared with TAA through computational simulations. Methods, A dynamic finite element foot model was built from the MRIs of a healthy participant and modified into two implanted counterparts (TTR and TAA) by incorporating the corresponding prosthetic components into the ankle joint. Twenty bony parts, thirty-nine ligament/tendon units, nine muscle contractors, and bulk soft tissue were included in the intact foot model. The TTR prosthesis was reconstructed from the mirror image data of the participant's contralateral talus and the TAA prosthesis was modelled by reproducing the Scandinavian ankle replacement procedure in the model assembly. The model was meshed with explicit deformable elements and validated against existing experimental studies that have assessed specific walking scenarios. Simulations were performed using the boundary conditions (time-variant matrix of muscle forces, segment orientation, and ground reaction forces) derived from motion capture analyses and musculoskeletal modelling of the participant's walking gait. Outcome variables, including foot kinematics, joint loading, and plantar pressure were reported and compared among the three model conditions. Linear regression indicated a better agreement between the TTR model and intact foot model in plots of joint motions and foot segment movements during walking (R² ​= ​0.721–0.993) than between the TAA and intact foot (R² ​= ​0.623–0.990). TAA reduced talocrural excursion by 21.36%–31.92% and increased (MTP) dorsiflexion by 3.03%. Compared with the intact foot, TTR and TAA increased the midtarsal joint contact force by 17.92% and 10.73% respectively. The proximal-to-distal force transmission within the midfoot was shifted to the lateral column in TTR (94.52% or 210.54 ​N higher) while concentrated on the medial column in TAA (41.58% or 27.55 ​N higher). The TTR produced a plantar pressure map similar to that of the intact foot. TAA caused the plantar pressure centre to drift medially and increased the peak forefoot pressure by 7.36% in the late stance. The TTR better reproduced the foot joint motions, segment movements, and plantar pressure map of an intact foot during walking. TAA reduced ankle mobility while increasing movement of the adjacent joints and forefoot plantar pressure. Both implant methods changed force transmission within the midfoot during gait progression. The translational potential of this article Our work is one of the few to report foot segment movements and the internal loading status of implanted ankles during a dynamic locomotion task. These outcomes partially support the conjecture that TTR is a prospective surgical alternative for pathological ankles from a biomechanical perspective. This study paves the way for further clinical investigations and systematic statistics to confirm the effects of TTR on functional joint recovery.

Background: Monitoring spine kinematics is crucial for applications like disease evaluation and ergonomics analysis. However, the small scale of vertebrae and the number of degrees of freedom present significant challenges for noninvasive and convenient spine kinematics estimation. Methods: This study developed a dynamic optimization framework for wearable spine motion tracking at the intervertebral joint level by integrating smartphone videos and Inertia Measurement Units (IMUs) with dynamic constraints from a thoracolumbar spine model. Validation involved motion data from 10 healthy males performing static standing, dynamic upright trunk rotations, and gait. This data included rotations of ten IMUs on vertebrae and virtual landmarks from three smartphone videos preprocessed by OpenCap, an application leveraging computer vision for pose estimation. The kinematic measures derived from the optimized solution were compared against simultaneously collected infrared optical marker-based measurements and in vivo literature data. Solutions only based on IMUs or videos were also compared for accuracy evaluation. Results: The proposed optimization approach closely matched the reference data in the intervertebral or segmental rotation range, demonstrating minimal angular differences across all motions and the highest correlation in 3D rotations (maximal Pearson and intraclass correlation coefficients of 0.92 and 0.94, respectively). Time-series changes of joint angles also aligned well with the optical-marker reference. Conclusion: Dynamic optimization of the spine simulation that integrates IMUs and computer vision outperforms the single-modality method. Significance: This markerless 3D spine motion capture method holds potential for spinal health assessment in large cohorts in real-world settings without dedicated laboratories.

Understanding the coordination between the pelvis and lower limbs in individuals with hemiplegic gait is crucial for deciphering their walking patterns. While studies have focused on lower limb kinematics in stroke patients, research on pelvis-lower limb coordination remains limited. This study aims to assess pelvis-lower limb coordination and kinematics in stroke patients using statistical parametric mapping (SPM) and smartphone-based markerless motion capture. Seventeen stroke patients and twenty healthy individuals were recruited to collect locomotion data using dual smartphone videos. For comparison, the time-series coordination of the pelvis-thigh, thigh-shank, and shank-foot among the control, paretic, and nonparetic limbs were analyzed using SPM and continuous relative phase (CRP). The results showed that there were significant differences (p < 0.05) in the CRP curves of the pelvis-thigh in the sagittal plane (50–62% of the gait cycle), pelvis-thigh in the coronal plane (0–100% of the gait cycle), thigh-shank (65–92% of the gait cycle), and shank-foot (13–29% and 57–68% of the gait cycle) across the different segments. Assessing the coordination and kinematics of the pelvis and lower limbs using a feasible and portable motion capture technique could assist clinicians in identifying potential muscle dysfunction while uncovering the compensatory strategies that individuals with hemiplegic gait may use to maintain balance, stability, and propulsion during walking. These results could guide clinicians in targeting interventions to reduce spasticity and strengthen muscles, ultimately enhancing coordination, optimizing gait mechanics, and improving functional outcomes.