Non-linear changes of lower extremity kinetics prior to gait transition

Differences between lower extremity joint running kinetics captured by marker-based and markerless systems were speed dependent

BACKGROUND

The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis. Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements, such as running. Applied studies using markerless systems in clinical and sports settings are still lacking. Thus, the present study compared running biomechanics estimated by marker-based and markerless systems. Given running speed not only affects sports performance but is also associated with clinical injury prevention, diagnosis, and rehabilitation, we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.

METHODS

Kinematic data from marker-based/markerless technologies were collected, along with ground reaction force data, from 16 young adults running on an instrumented treadmill at 3 speeds: 2.24 m/s, 2.91 m/s, and 3.58 m/s (5.0 miles/h, 6.5 miles/h, and 8.0 miles/h). Sagittal plane moments and powers of the hip, knee, and ankle were calculated by inverse dynamic methods. Time series analysis and statistical parametric mapping were used to determine system differences.

RESULTS

Compared to the marker-based system, the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.

CONCLUSION

Despite the promising application of markerless technology in clinical settings, systematic markerless overestimation requires focused attention. Based on segment pose estimations, the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers, which led to greater joint moments and powers estimates by markerless vs. marker-based systems. The differences were amplified by running speed.

Investigation of normal knees kinematics in walking and running at different speeds using a portable motion analysis system

Walking and running at different speeds are common in daily life. This study investigated 6 degrees of freedom (DOF) kinematics of normal knees of Chinese during walking and running. Forty healthy participants were investigated in 4 conditions: comfortable walking, normal walking, slow running and ordinary running. The range of motion (ROM) and peak values in 6 DOF kinematics were analysed. As the speed increased, a general increase in flexion, lateral and proximal translations occurred. Significant increases of ROM in flexion/extension, axial rotation and medial/lateral translations were observed. The ROM of adduction/abduction, anterior/posterior and proximal/distal translations were greatest during normal walking. The maximum and minimum flexion/extension, maximum internal rotation and tibial lateral translations increased with the increase of speed. The maximum and minimum tibial proximal translations in running were found being greater than walking. A phenomenon between walking and running was observed: both tibial proximal/distal and medial/lateral translations increased when changed from walking to running. Non-linear transition exists in 6 DOF kinematics during walking to running. Discoveries in this study may have potential clinical values to serve as references of normal walking and running in the management of knee injury and knee rehabilitation.

Effects of shoe collar types on ankle and knee biomechanics characteristics when performing the side-step cutting task

This study aimed to examine the effect of football shoes with different collar types on ankle and knee kinematic and kinetics features during 45° and 135° side-step cutting tasks. Fifteen healthy college football players volunteered for the study. Each participant was instructed to perform side-step cutting tasks with high, low, and no collar football shoes. The kinematic and ground reaction force data were measured using a Vicon motion capture system and a Kistler force plate, respectively. Two-way MANOVAs with repeated measures were used to examine the effect of shoe collar type and task conditions. There were no interaction effects. The high collar football shoe showed decreased ankle range of motion in the sagittal plane (p = 0.010) and peak ankle external rotation moment (p = 0.009) compared to the no collar football shoe. The high (p = 0.025) and low (p = 0.029) collar football shoes presented greater peak ankle external rotation angles than the no collar football shoe. These results imply that football shoes with high collars made of high intensity knitted fabric could be used to restrict ankle joint movement, with potential implications for decreasing the risk of ankle sprain injuries in football players.

Effects of Dynamic IMU-to-Segment Misalignment Error on 3-DOF Knee Angle Estimation in Walking and Running

The inertial measurement unit (IMU)-to-segment (I2S) alignment is an important part of IMU-based joint angle estimation, and the accurate estimation of the three degree of freedom (3-DOF) knee angle can provide practical support for the evaluation of motions. In this paper, we introduce a dynamic weight particle swarm optimization (DPSO) algorithm with crossover factor based on the joint constraint to obtain the dynamic alignment vectors of I2S, and use them to perform the quaternion-based 3-DOF knee angle estimation algorithm. The optimization algorithm and the joint angle estimation algorithm were evaluated by comparing with the optical motion capture system. The range of 3-DOF knee angle root mean square errors (RMSEs) is 1.6°-5.9° during different motions. Furthermore, we also set up experiments of human walking (3 km/h), jogging (6 km/h) and ordinary running (9 km/h) to investigate the effects of dynamic I2S misalignment errors on 3-DOF knee angle estimation during different motions by artificially adding errors to I2S alignment parameters. The results showed differences in the effects of I2S misalignment errors on the estimation of knee abduction, internal rotation and flexion, which indicate the differences in knee joint kinematics among different motions. The IMU to thigh misalignment error has the greatest effect on the estimation of knee internal rotation. The effect of IMU to thigh misalignment error on the estimation of knee abduction angle becomes smaller and then larger during the two processes of switching from walking to jogging and then speeding up to ordinary running. The effect of IMU to shank misalignment error on the estimation of knee flexion angle is numerically the largest, while the standard deviation (SD) is the smallest. This study can provide support for future research on the accuracy of 3-DOF knee angle estimation during different motions.

Comparison of Lower Extremity Joint Moment and Power Estimated by Markerless and Marker-Based Systems during Treadmill Running

Background: Markerless (ML) motion capture systems have recently become available for biomechanics applications. Evidence has indicated the potential feasibility of using an ML system to analyze lower extremity kinematics. However, no research has examined ML systems’ estimation of the lower extremity joint moments and powers. This study aimed to compare lower extremity joint moments and powers estimated by marker-based (MB) and ML motion capture systems. Methods: Sixteen volunteers ran on a treadmill for 120 s at 3.58 m/s. The kinematic data were simultaneously recorded by 8 infrared cameras and 8 high-resolution video cameras. The force data were recorded via an instrumented treadmill. Results: Greater peak magnitudes for hip extension and flexion moments, knee flexion moment, and ankle plantarflexion moment, along with their joint powers, were observed in the ML system compared to an MB system (p < 0.0001). For example, greater hip extension (MB: 1.42 ± 0.29 vs. ML: 2.27 ± 0.45) and knee flexion (MB: −0.74 vs. ML: −1.17 nm/kg) moments were observed in the late swing phase. Additionally, the ML system’s estimations resulted in significantly smaller peak magnitudes for knee extension moment, along with the knee production power (p < 0.0001). Conclusions: These observations indicate that inconsistent estimates of joint center position and segment center of mass between the two systems may cause differences in the lower extremity joint moments and powers. However, with the progression of pose estimation in the markerless system, future applications can be promising.

Research on Kinematic Parameters of Multiple Gait Pattern Transitions

Gait recognition technology is the key technology in the field of exoskeletons. In the current research of gait recognition technology, there is less focus on the recognition of the transition between gait patterns. This study aims to determine which kinematic parameters have significant differences in the transitions (between level and stair walking and between level and ramp walking) of different gait patterns, to determine whether these parameters change differently in different gait pattern transitions, and the order the significant differences occur through a comparative analysis of various kinematic parameters between the transition stride and the before stride in the former pattern. We analyzed 18 parameters concerning both lower limbs and trunk. We compared each time point of the transition strides to the corresponding time points of the before stride using a series of two-sample t-tests, and we then evaluated the difference between the transition stride and the before stride based upon the number of time points within the gait cycle that were statistically different. We found that the sagittal plane angular velocity and the angular acceleration of all joints and the resultant velocity of the thigh and shank of the leading limb had significant differences in the process of transition; the sagittal plane angular velocity of all joints of the trailing limb and the velocity of the trunk in the coronary axis direction also showed a significant difference. The angular acceleration of all joints, the sagittal plane angular velocity of the ankle joint of the leading limb, and the acceleration of the trunk in the coronal axis direction showed a difference in the early stage of the transition. In general, the leading limb had a significant difference earlier than the trailing limb, and the acceleration parameters changed earlier than the velocity parameters. These parameters showed different combinations of changes in the transition of different gait patterns, and the changes in these parameters reflected different gait pattern transitions. Therefore, we believe that the results of this study can provide a reference for the gait pattern transition recognition of wearable exoskeletons.

Paired nonlinear behavior of active and passive joint torques associated with preparation for walk-to-run gait transition

This study investigated the lower extremity torque's active and passive features during the walk-to-run gait transition with continuously increased walking speed. Fourteen volunteers participated in the experiment. Kinematic and kinetic data were collected synchronously. Five strides leading up the gait transition were examined. Peaks of the passive (e.g., contact) and active (e.g., generalized muscle torques), along with net joint torque, and time to peak torques exhibited significant differences at the last stride before gait transition, compared to the first four strides, at the ankle, knee, and hip joints, respectively. Selected peak joint active and passive torques showed significant and opposite trends at critical events within a stride cycle: such ankle joint right after heel-contact, knee joint during weight acceptance, and both hip and knee joints right before toe-off. The magnitude and the corresponding time to active and passive peak torque changed in a nonlinear pattern before the transition from walk to run. The lower extremity segment-interaction during gait transition appeared to be an active reorganization exemplified by the interaction between the lower extremity's active and passive torque components.

Orthodontic force prediction model of T-loop closing spring based on dynamic resistance model

Malocclusion has been seriously endangering human oral function. The most effective and mature therapy is orthodontic treatment. But the relationship between the shape of the T-loop and the orthodontic force is unclear, and the precise mathematical model has not been established. In this article, the dynamic orthodontic force prediction model of the T-loop was established by analyzing the treatment process of the T-loop. The model was based on the dynamic resistance model of waxy dental jaw, the theory of beam deformation, and the deformation characteristics of the T-loop. In the experimental process, 11 kinds of orthodontic archwires were used as experimental samples, including 2 kinds of common archwire materials, 7 kinds of cross-sectional sizes, and 10 kinds of clearance distances. The T-loop was put into the extraction space and immersed in 75°C constant temperature water for 2 min. And the experimental data were measured and collected by the dynamic force measuring device. The experimental results show that the cross-sectional size and the clearance distance are positively correlated with the orthodontic force. The influence of the clearance distance on the orthodontic force is greater than that of the cross-section size. The deviation rates between the experimental values of orthodontic force and the theoretical values are between 1.10% and 9.09%, which verifies the accuracy of the dynamic orthodontic force prediction model. The model can predict the orthodontic force, improve the treatment effect, shorten the treatment cycle, and provide reference and guidance for orthodontists to carry out orthodontic treatment safely and effectively.

Establishment and Experiment of Utility Archwire Dynamic Orthodontic Moment Prediction Model

OBJECTIVE

This study investigated the performance of a dynamic orthodontic moment prediction model by analyzing orthodontic treatment processes with different utility archwires.

METHOD

The prediction model was based on a wax resistance model, the combined load theory of beams and the lateral buckling theory of prisms. The experimental samples used herein comprised 12 different archwire configurations (3 different materials and 4 different diameters). The utility archwire was ligated to the 11th tooth of the wax mold, which was immersed in a constant temperature water environment at 75 °C for 2 min.

RESULT

As the archwire diameter increased, increasing the elastic modulus of the archwire produced greater increases in the change rate of the orthodontic moment with respect to the lateral arc length. A comparison of the orthodontic moment values from three common orthodontic archwire materials revealed the following trend: stainless steel wire > Australian wire > Ni-Ti wire.

CONCLUSION

The accuracy of the utility archwire dynamic orthodontic moment prediction model was verified through a comparison of the experimental measurements and theoretical calculations.

SIGNIFICANCE

The presented model can help make timely adjustments to orthodontic treatment schemes, improve the orthodontic effect, shorten the treatment cycle, and provide reference and guidance that enables orthodontists to carry out orthodontic treatment safely and efficiently.