Comparison of Two Methods for In Vivo Estimation of the Glenohumeral Joint Rotation Center (GH-JRC) of the Patients with Shoulder Hemiarthroplasty

Determination of an accurate glenohumeral-joint rotation center (GH-JRC) from marker data is essential for kinematic and dynamic analysis of shoulder motions. Previous studies have focused on the evaluation of the different functional methods for the estimation of the GH-JRC for healthy subjects. The goal of this paper is to compare two widely used functional methods, namely the instantaneous helical axis (IHA) and symmetrical center of rotation (SCoRE) methods, for estimating the GH-JRC in vivo for patients with implanted shoulder hemiarthroplasty. The motion data of five patients were recorded while performing three different dynamic motions (circumduction, abduction, and forward flexion). The GH-JRC was determined using the CT-images of the subjects (geometric GH-JRC) and was also estimated using the two IHA and SCoRE methods. The rotation centers determined using the IHA and SCoRE methods were on average 1.47±0.62 cm and 2.07±0.55 cm away from geometric GH-JRC, respectively. The two methods differed significantly (two-tailed p-value from paired t-Test ∼0.02, post-hoc power ∼0.30). The SCoRE method showed a significant lower (two-tailed p-value from paired t-Test ∼0.03, post-hoc power ∼0.68) repeatability error calculated between the different trials of each motion and each subject and averaged across all measured subjects (0.62±0.10 cm for IHA vs. 0.43±0.12 cm for SCoRE). It is concluded that the SCoRE appeared to be a more repeatable method whereas the IHA method resulted in a more accurate estimation of the GH-JRC for patients with endoprostheses

A Patient-Specific Foot Model for the Estimate of Ankle Joint Forces in Patients with Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the leading cause of childhood disability from a musculoskeletal disorder. It generally affects large joints such as the knee and the ankle, often causing structural damage. Different factors contribute to the damage onset, including altered joint loading and other mechanical factors, associated with pain and inflammation. The prediction of patients' joint loading can hence be a valuable tool in understanding the disease mechanisms involved in structural damage progression. A number of lower-limb musculoskeletal models have been proposed to analyse the hip and knee joints, but juvenile models of the foot are still lacking. This paper presents a modelling pipeline that allows the creation of juvenile patient-specific models starting from lower limb kinematics and foot and ankle MRI data. This pipeline has been applied to data from three children with JIA and the importance of patient-specific parameters and modelling assumptions has been tested in a sensitivity analysis focused on the variation of the joint reaction forces. This analysis highlighted the criticality of patient-specific definition of the ankle joint axes and location of the Achilles tendon insertions. Patient-specific detection of the Tibialis Anterior, Tibialis Posterior, and Peroneus Longus origins and insertions were also shown to be important

Shoulder joint contact force during lever-propelled wheelchair propulsion

The aim of this study was to obtain quantitative results about shoulder contact force during wheelchair lever propulsion when the gear ratio of the lever propulsion mechanism is changing. The effect of the gear ratio on the shoulder contact force was investigated for few different wheelchair loading. For the experiments we designed a special mechatronic wheelchair simulator that allowed the simulation of different gear ratios ofthe wheelchair lever propulsion mechanism and simulation of different road inclinations. The same simulator was also used for simulation of a hand rim propelled wheelchair. We conducted also a hand rim propulsion experiment and used the results from it for comparison with the lever propulsion data. Four nondisabled male adults with no prior wheeling experience participated in the experiment. In the first tests, a lever propelled wheelchair was simulated with the simulator. The target speed of the wheelchair was set to 2 km/h. For the test the gear ratio was varied from 1.5 to 1/1.5. A load torque was applied to the rear wheels to imitate road inclinations of 0, 2° and 4°.ln the second part of the test, the simulator was structured to simulate a hand rim propelled wheelchair. The participants were asked to keep the same speed (2 km/h) and the simulator was set sequentially to imitate climbing a ramp inclined on 0°,2° and 4°. Kinematic data of the body were collected by a motion capture system. Kinetic data such as hand force and driving torque, were measured by instrumented wheels with incorporated six-axis force sensor. The intersegmental joint forces and moments were calculated from the obtained kinematic and kinetic data via inverse dynamics analysis procedure. Muscle forces were computed from the measured joint moments by using an optimization approach. Shoulder joint contact force, which indicates the joint surface loading, was computed as a synthetic vector of the intersegmental force for shoulder joint acquired from the inverse dynamics analysis and the compressive forces from muscles, tendons, ligaments and cartilages crossing the shoulder joint It was observed that the decrease of the gear ratio causes increased cycle frequency and reduces the shoulder joint contact force. Result showed that the shoulder joint contact force during lever propulsion with a gear ratio 1/1.5 was up to 70% lower than the shoulder joint contact force during handrim propulsion. The results from this study could be used in the design of new lever propulsion mechanisms that reduce the risks of secondary shoulder disorders and increase user's comfort

sEMG-assisted inverse modelling of 3D lip movement: a feasibility study towards person-specific modelling

We propose a surface-electromyographic (sEMG) assisted inverse-modelling (IM) approach for a biomechanical model of the face to obtain realistic person-specific muscle activations (MA) by tracking movements as well as innervation trajectories. We obtained sEMG data of facial muscles and 3D positions of lip markers in six volunteers and, using a generic finite element (FE) face model in ArtiSynth, performed inverse static optimisation with and without sEMG tracking on both simulation data and experimental data. IM with simulated data and experimental data without sEMG data showed good correlations of tracked positions (0.93 and 0.67) and poor correlations of MA (0.27 and 0.20). When utilising the sEMG-assisted IM approach, MA correlations increased drastically (0.83 and 0.59) without sacrificing performance in position correlations (0.92 and 0.70). RMS errors show similar trends with an error of 0.15 in MA and of 1.10 mm in position. Therefore, we conclude that we were able to demonstrate the feasibility of an sEMG-assisted inverse modelling algorithm for the perioral region. This approach may help to solve the ambiguity problem in inverse modelling and may be useful, for instance, in future applications for preoperatively predicting treatment-related function los