A Mathematical Formulation for 3D Quasi-Static Multibody Models of Diarthrodial Joints

This study describes a genera] set of equations for quasi-static analysis of three-dimensional multibody systems, with a particular emphasis on modeling of diarthrodial joints. The model includes articular contact, muscle forces, tendons and tendon pulleys, ligaments, and the wrapping of soft tissue structures around bone and cartilage surfaces. The general set of equations governing this problem are derived using a consistent notation for all types of links, which can be converted conveniently into efficient computer codes. The computational efficiency of the model is enhanced by the use of analytical Jacobians, particularly in the analysis of articular surface contact and wrapping of soft tissue structures around bone and cartilage surfaces. The usefulness of the multibody model is demonstrated by modeling the patellofemoral joint of six cadaver knees, using cadaver-specific data for the articular surface and bone geometries, as well as tendon and ligament insertions and muscle lines of actions. Good accuracy was observed when comparing the model patellar kinematic predictions to experimental data (mean ± stand, dev. error in translation: 0.63 ± 1.19 mm, 0.10 ± 0.71 mm, -0.29 ± 0.84 mm along medial, proximal, and anterior directions, respectively; in rotation: -1.41 ± 1.71°, 0.27 ±2.38°, -1.13 ± 1.83° in flexion, tilt and rotation, respectively). The accuracy which can be achieved with this type of model, and the computational efficiency of the algorithm employed in this study may serve in many applications such as computer-aided surgical planning, and real-time computer-assisted surgery in the operating room.     

Kinematics of nonstationary locomotion in the centipede <Emphasis Type="Italic">Scolopendra cingulata</Emphasis>: A single instant change of speed

The spatiotemporal parameters of leg movement in Scolopendra instantly changing the locomotion speed from V ₁ to V ₂ ≠ V ₁ are investigated. It is shown that (i) the principle of “in trail” leg placement is kept upon a change of speed; (ii) the continuity of the metachronal coordination is not disturbed; but (iii) for some time after changing speed the set of ipsilateral legs comprises (a) head-proximal legs creating a new trackway of steps with pace ℓ₂, and (b) distal legs still using the old trackway with pace ℓ₁. The two groups differ in kinematic parameters. Group (a) works in the stationary mode corresponding to speed V ₂, while group (b) works in a transitory mode. Consecutively, with a metachronal wave propagating backwards along the body but immobile relative to the ground, more and more legs from group (b) switch to the new stationary mode.     

Characteristics of Surface Electromyography of Forehand Smash of Badminton Players

To understand the characteristics of the forehand smash of badminton player and improve their performance, this study took eight badminton players as the subject, obtained the kinematics data through the Qualisys infrared high-speed camera, obtained the electromyography (EMG) data through the ME-6000 surface EMG test system, and compared and analyzed their forehand smash action. The results showed that the greater the angle and speed of different joints in the forehand smash was, the greater the speed and strength of hitting the ball was; the discharge amount of biceps brachii (BB) was the smallest, followed by triceps brachii (TB), flexor carpi ulnaris (FCU), anterior deltoid (AD), posterior deltoid (FD), and pectoralis major (PM), and the activation order was PM → AD → FD → BB → TB → FCU; deltoid muscle and pectoralis major muscle were the main muscle groups in the exercise, which showed the characteristic that trunk muscles drove arm muscles.     

Sub-millimetre accurate human hand kinematics: from surface to skeleton

A highly accurate human hand kinematics model and identification are proposed. The model includes the five digits and the palm arc based on mapping function between surface landmarks and estimated joint centres of rotation. Model identification was experimentally performed using a motion tracking system. The evaluation of the marker position estimation error, which is on sub-millimetre level across all digits, underlines model quality and accuracy. Noticeably, with the development of this model, we were able to improve various modelling assumptions from literature and found a basic linear relationship between surface and skeleton rotational angles.     

Evaluation of regression-based 3-D shoulder rhythms

The movements of the humerus, the clavicle, and the scapula are not completely independent. The coupled pattern of movement of these bones is called the shoulder rhythm. To date, multiple studies have focused on providing regression-based 3-D shoulder rhythms, in which the orientations of the clavicle and the scapula are estimated by the orientation of the humerus. In this study, six existing regression-based shoulder rhythms were evaluated by an independent dataset in terms of their predictability. The datasets include the measured orientations of the humerus, the clavicle, and the scapula of 14 participants over 118 different upper arm postures. The predicted orientations of the clavicle and the scapula were derived from applying those regression-based shoulder rhythms to the humerus orientation. The results indicated that none of those regression-based shoulder rhythms provides consistently more accurate results than the others. For all the joint angles and all the shoulder rhythms, the RMSE are all greater than 5°. Among those shoulder rhythms, the scapula lateral/medial rotation has the strongest correlation between the predicted and the measured angles, while the other thoracoclavicular and thoracoscapular bone orientation angles only showed a weak to moderate correlation. Since the regression-based shoulder rhythm has been adopted for shoulder biomechanical models to estimate shoulder muscle activities and structure loads, there needs to be further investigation on how the predicted error from the shoulder rhythm affects the output of the biomechanical model.