The aim of this study was to calculate the stress acting on the trapeziometacarpal joint during an key pinch grip.
We used profile X-rays of the thumb to measure the various bony and muscle lever arms. We assessed the angles of action of the muscular elements involved in the thumb column. Based on this data, we established a two-dimensional geometric model that enabled us to determine the forces at each joint level, as a function of stresses and muscular contributions. We were also able to calculate the participation of the different muscle groups in obtaining a balanced situation.
Our results, as a function of the degree of flexion of the interphalangeal and metacarpophalangeal joints, show a multiplying factor of 2.9-3.19 in relation to the key pinch grip force.
Previous studies modelling a key pinch grip are showed multiplying factors from 6 to 13 in relation to the key pinch grip force. They are not compatible with the characteristics of the polyethylene used for trapeziometacarpal prostheses, whereas numerous articles in the literature show survival rates that are more or less comparable to those of total hip prostheses. These studies required an excessive number of assumptions, which could lead to error. Our results are compatible with the results of trapeziometacarpal prosthesis and with those of a recent study measuring intra-articular trapeziometacarpal pressure in a cadaveric model. Our model allows us to test different configurations of the thumb spine depending on the degree of flexion of the interphalangeal and metacarpophalangeal joints.

The position calibration of inertial measurement units (IMUs) is an important part of human motion capture, especially in wearable systems. In realistic applications, static calibration is quickly invalid during the motions for IMUs loosely mounted on the body. In this paper, we propose a dynamic position calibration algorithm for IMUs mounted on the waist, upper leg, lower leg, and foot based on joint constraints. To solve the problem of IMUs\' position displacement, we introduce the Gauss-Newton (GN) method based on the Jacobian matrix, the dynamic weight particle swarm optimization (DWPSO), and the grey wolf optimizer (GWO) to realize IMUs\' position calibration. Furthermore, we establish the coordinate system of human lower limbs to estimate each joint angle and use the fusion algorithm in the field of quaternions to improve the attitude calibration performance of a single IMU. The performances of these three algorithms are analyzed and evaluated by gait tests on the human body and comparisons with a high-precision IMU-Mocap reference device. The simulation results show that the three algorithms can effectively calibrate the IMU\'s position for human lower limbs. Additionally, when the degree of freedom (DOF) of a certain dimension is limited, the performances of the DWPSO and GWO may be better than GN, when the joint changes sufficiently, the performances of the three are close. The results confirm that the dynamic calibration algorithm based on joint constraints can effectively reduce the position offset errors of IMUs on upper or lower limbs in practical applications.

The planar, one degree of freedom (1-DoF) four-bar linkage is an important model for understanding the function, performance and evolution of numerous biomechanical systems. One such system is the opercular mechanism in fishes, which is thought to function like a four-bar linkage to depress the lower jaw. While anatomical and behavioral observations suggest some form of mechanical coupling, previous attempts to model the opercular mechanism as a planar four-bar have consistently produced poor model fits relative to observed kinematics. Using newly developed, open source mechanism fitting software, we fitted multiple three-dimensional (3D) four-bar models with varying DoF to in vivo kinematics in largemouth bass to test whether the opercular mechanism functions instead as a 3D four-bar with one or more DoF. We examined link position error, link rotation error and the ratio of output to input link rotation to identify a best-fit model at two different levels of variation: for each feeding strike and across all strikes from the same individual. A 3D, 3-DoF four-bar linkage was the best-fit model for the opercular mechanism, achieving link rotational errors of less than 5%. We also found that the opercular mechanism moves with multiple degrees of freedom at the level of each strike and across multiple strikes. These results suggest that active motor control may be needed to direct the force input to the mechanism by the axial muscles and achieve a particular mouth-opening trajectory. Our results also expand the versatility of four-bar models in simulating biomechanical systems and extend their utility beyond planar or single-DoF systems.

Motion analysis aims at evaluating the joint kinematics but the relative movement between the bones and the skin markers, known as soft tissue artifact (STA), introduces large errors. Multi-body optimization (MBO) methods were proposed to compensate for the STA. However, the validation of the MBO methods using no or simple kinematic constraints (e.g., spherical joint) demonstrated inaccurate in vivo kinematics. Anatomical constraints were introduced in MBO methods and various ligament constraints were proposed in the literature. The validation of these methods has not been performed yet. The objective of this study was to validate, against in vivo knee joint kinematics measured by intra-cortical pins on three subjects, the model-based kinematics obtained by MBO methods using three different types of ligament constraints. The MBO method introducing minimized or prescribed ligament length variations showed some improvements in the estimation of knee kinematics when compared to no kinematic constraints, to degree-of-freedom (DoF) coupling curves, and to null ligament length variations. However, the improvements were marginal when compared to spherical constraints. The errors obtained by minimized and prescribed ligament length variations were below 2.5° and 4.1mm for the joint angles and displacements while the errors obtained with spherical joint constraints were below 2.2° and 3.1mm. These errors are generally lower than the errors previously reported in the literature. As a conclusion, this study presented encouraging results for the compensation of the STA by MBO and for the introduction of anatomical constraints in MBO. Personalization of the geometry should be considered for further improvements.

We developed and evaluated a new kinematic driver for musculoskeletal models using ambulatory inertial and magnetic measurement units (IMMUs). The new driver uses the orientation estimates based on sensor fusion of each individual IMMU and benefits from two important properties of musculoskeletal models. First, these models contain more complex, anatomical, kinematic models than those currently used for sensor fusion of multiple IMMUs and are continuously improved. Second, they allow movement between segment and measured sensor. For three different tasks, the new IMMU driver, (optical) marker drivers and a combination of both were used to reconstruct the motion. Maximal root mean square (RMS) joint angle differences with respect to the silver standard (combined IMMU/marker drivers) were found for the hip joint; 4°, 2° and 5° during squat, gait and slideboard tasks for IMMU-driven reconstructions, compared with 6°, 5° and 5° for marker-driven reconstructions, respectively. The measured angular velocities corresponded best to the IMMU-driven reconstructions, with a maximal RMS difference of 66°/s, compared with 108°/s and 91°/s for marker-driven reconstructions and silver standard. However, large oscillations in global accelerations occurred during IMMU-driven reconstructions resulting in a maximal RMS difference with respect to measured acceleration of 23 m/s2, compared with 9 m/s2 for reconstructions that included marker drivers. The new driver facilitates direct implementation of IMMU-based orientation estimates in currently available biomechanical models. As such, it can help in the rapid expansion of biomechanical analysis based on outdoor measurements.