Lower-limb kinematics and kinetics during continuously varying human locomotion
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ABSTRACT:
SUBMITTER: Reznick E
PROVIDER: S-EPMC8553836 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Powered knee and ankle prostheses can perform a limited number of discrete ambulation tasks. This is largely due to their control architecture, which uses a finite-state machine to select among a set of task-specific controllers. A non-switching controller that supports a continuum of tasks is expected to better facilitate normative biomechanics. This paper introduces a predictive model that represents gait kinematics as a continuous function of gait cycle percentage, speed, and incline. The basis model consists of two parts: basis functions that produce kinematic trajectories over the gait cycle and task functions that smoothly alter the weight of basis functions in response to task. Kinematic data from 10 able-bodied subjects walking at 27 combinations of speed and incline generate training and validation data for this data-driven model. Convex optimization accurately fits the model to experimental data. Automated model order reduction improves predictive abilities by capturing only the most important kinematic changes due to walking tasks. Constraints on a range of motion and jerk ensure the safety and comfort of the user. This model produces a smooth continuum of trajectories over task, an impossibility for finite-state control algorithms. Random sub-sampling validation indicates that basis modeling predicts untrained kinematics more accurately than linear interpolation.
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Project description:Static lower extremity alignment (LEA) during normal stance has been used clinically as a tool to determine the presence of known anterior cruciate ligament (ACL) risk factors during dynamic tasks. Previous work investigating the relationship between static LEA during normal stance and risk factors for ACL injury is limited by the use of imprecise methods or because it focuses on knee valgus only and no other potentially important variables. The aim of this investigation was to determine the relationships between static LEA and the corresponding LEA during drop landings. Forty-one female athletes were recruited for the study (age: 19.8 ± 2.5 years, height: 1.73 ± 0.06 m, mass: 64.03 ± 6.66 kg). Lower limb kinematic data were collected using a 10 camera infrared motion capture system (500 Hz) with retro-reflective markers placed over key anatomical landmarks. This system was linked to two force platforms (1000 Hz) with subsequent three-dimensional kinematic and kinetic data developed using standard software (Visual3D). Following an appropriate warm-up, data collection involved participants standing with their arms partially abducted to record static LEA. This was following by a series of drop landings from a 0.4 m box onto the force platforms. Maximum LEA data during drop landings were then compared with static LEA. Analyses showed that in comparison to static stance, during landings the anterior tilt of the pelvis decreased while hip abduction and knee internal rotation increased. At best, static LEA variables were moderately correlated (r = -0.51 to 0.58) with peak values measured during drop landings. Additionally, regression analysis did not yield any significant predictors of any key peak hip or knee variables measured during drop landings (p = 0.15 to 0.89). When combined, the poor relationships observed between kinematics during static LEA and LEA during drop landings calls into question the practice of using static measures to predict LEA during even simple landing tasks. These findings suggest static assessments of LEA may have minimal value as an ACL injury screening tool.
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Project description:Powered prosthetic legs can improve the quality of life for people with transfemoral amputations by providing net positive work at the knee and ankle, reducing the effort required from the wearer, and making more tasks possible. However, the controllers for these devices use finite state machines that limit their use to a small set of pre-defined tasks that require many hours of tuning for each user. In previous work, we demonstrated that a continuous parameterization of joint kinematics over walking speeds and inclines provides more accurate predictions of reference kinematics for control than a finite state machine. However, our previous work did not account for measurement errors in gait phase, walking speed, and ground incline, nor subject-specific differences in reference kinematics, which occur in practice. In this work, we conduct a pilot experiment to characterize the accuracy of speed and incline measurements using sensors onboard our prototype prosthetic leg and simulate phase measurements on ten able-bodied subjects using archived motion capture data. Our analysis shows that given demonstrated accuracy for speed, incline, and phase estimation, a continuous parameterization provides statistically significantly better predictions of knee and ankle kinematics than a comparable finite state machine, but both methods' primary source of predictive error is subject deviation from average kinematics.
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Project description:PurposeTo investigate if lumbar and lower limb kinematics or kinetics are different between groups with and without a history of LBP during lifting. Secondly, to investigate relationships between biomechanical variables and pain ramp during repeated lifting.Methods21 LBP and 20 noLBP participants completed a 100-lift task, where lumbar and lower limb kinematics and kinetics were measured during lifting, with a simultaneous report of LBP intensity every 10 lifts. Lifts were performed in a laboratory setting, limiting ecological validity.ResultsThe LBP group used a different lifting technique to the noLBP group at the beginning of the task (slower and more squat-like). Kinetic differences at the beginning included less peak lumbar external anterior shear force and greater peak knee power demonstrated by the LBP group. However, at the end of the task, both groups lifted with a much more similar technique that could be classified as more stoop-like and faster. Peak knee power remained greater in the LBP group throughout and was the only kinetic difference between groups at the end of the lifting task. While both groups lifted using a more comparable technique at the end, the LBP group still demonstrated a tendency to perform a slower and more squat-like lift throughout the task. Only one of 21 variables (pelvic tilt at box lift-off), was associated with pain ramp in the LBP group. Conclusions: Workers with a history of LBP, lift with a style that is slower and more squat-like than workers without any history of LBP. Common assumptions that LBP is associated with lumbar kinematics or kinetics such as greater lumbar flexion or greater forces were not observed in this study, raising questions about the current paradigm around 'safe lifting'.
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Project description:The spatial distribution of myoelectric activity within lower limb muscles is often nonuniform and can change during different stationary tasks. Recent studies using high-density electromyography (EMG) have suggested that spatial muscle activity may also differ among muscles during locomotion, but contrasting electrode array sizes and experimental designs have limited cross-study comparisons. Here, we sought to determine if spatial EMG patterns differ among lower limb muscles and locomotion speeds. We recorded high-density EMG from the vastus medialis, tibialis anterior, biceps femoris, medial gastrocnemius, and lateral gastrocnemius muscles of 11 healthy subjects while they walked (1.2 and 1.6 m/s) and ran (2.0, 3.0, 4.0, and 5.0 m/s) on a treadmill. To overcome the detrimental effects of cable, electrode, and soft tissue movements on high-density EMG signal quality during locomotion, we applied multivariate signal cleaning methods. From these data, we computed the spatial entropy and center of gravity from the total myoelectric activity within each recording array during the stance or swing phases of the gait cycle. We found heterogeneous spatial EMG patterns evidenced by contrasting spatial entropy among lower limb muscles. As locomotion speed increased, mean entropy values decreased in four of the five recorded muscles, indicating that EMG signal amplitudes were more spatially heterogeneous, or localized, at faster speeds. The EMG center of gravity location also shifted in multiple muscles as locomotion speed increased. Contrasting myoelectric spatial distributions among muscles likely reflect differences in muscle architecture, but increasingly localized activity and spatial shifts in the center of gravity location at faster locomotion speeds could be influenced by preferential recruitment of faster motor units under greater loads.
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Project description:Standing up from a prone position is a critical daily activity for animals: failing to do so effectively may cause an injurious fall or increase predation susceptibility. This sit-to-stand behaviour (StS) is biomechanically interesting because it necessitates transitioning through near-maximal joint motion ranges from a crouched (i.e., poor mechanical advantage) to a more upright posture. Such large joint excursions should require large length changes of muscle-tendon units. Here we integrate experimental and musculoskeletal simulation methods to quantify the joint motions, limb forces, and muscle fibre forces, activations and length changes during StS in an extreme athlete-the greyhound-which has large hindlimb muscles bearing short-fibred distal muscles and long tendons. Study results indicate that hindlimb anti-gravity muscle fibres operate near their ~50% limits of length change during StS; mostly by starting at highly lengthened positions. StS also requires high muscle activations (>50%), in part due to non-sagittal motions. Finally, StS movements require passive non-muscular support in the distal hindlimb where short-fibred muscles are incapable of sustaining StS themselves. Non-locomotor behaviours like StS likely impose important trade-offs between muscle fibre force capacity and length changes, as well as active and passive mechanisms of support, that have been neglected in locomotor biomechanics studies.
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Project description:The relationship between trunk and lower limb kinematics in healthy females versus males is unclear since trunk kinematics in the frontal and transverse planes have not been systematically examined with lower limb kinematics. The aim of this study was to investigate the existence of different multi-joints movement strategies between genders during a single leg squat. We expected that compared to males, females would have greater trunk and pelvis displacement due to less trunk control and display hip and knee movement consistent with medial-collapse (i.e. greater hip adduction, hip medial rotation, knee abduction, and knee lateral rotation) on the weight-bearing limb. Nine females and 10 males participated in the study. Kinematic data were collected using an 8-camera, 3D-motion-capture-system. Trunk relative to pelvis, pelvis relative to the laboratory, hip and knee angles in three planes (sagittal, frontal and transverse) were examined at two time events relevant to knee joint mechanics: 45° of knee flexion and peak knee flexion. Females flexed their trunk less than males and rotated their trunk and pelvis toward the weight-bearing limb more than males. Females also displayed greater hip adduction and knee abduction than males. Taken together these results suggest that females and males used different movement strategies during a single leg squat. Females displayed a trunk and pelvic movement pattern that may put them at risk of knee injury and pain.
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Project description:Making rapid and proper compensatory postural adjustments is vital to prevent falls and fall-related injuries. This study aimed to investigate how, especially how rapidly, the multiple lower-limb muscles and joints would respond to the unexpected standing balance perturbations. Unexpected waist-pull perturbations with small, medium and large magnitudes were delivered to twelve healthy young adults from the anterior, posterior, medial and lateral directions. Electromyographical (EMG) and mechanomyographical (MMG) responses of eight dominant-leg muscles (i.e., hip abductor/adductors, hip flexor/extensor, knee flexor/extensor, and ankle dorsiflexor/plantarflexors) together with the lower-limb joint angle, moment, and power data were recorded. The onset latencies, time to peak, peak values, and/or rate of change of these signals were analyzed. Statistical analysis revealed that: (1) agonist muscles resisting the delivered perturbation had faster activation than the antagonist muscles; (2) ankle muscles showed the largest rate of activation among eight muscles following both anteroposterior and mediolateral perturbations; (3) lower-limb joint moments that complied with the perturbation had faster increase; and (4) larger perturbation magnitude tended to evoke a faster response in muscle activities, but not necessarily in joint kinetics/kinematics. These findings provided insights regarding the underlying mechanism and lower-limb muscle activities to maintain reactive standing balance in healthy young adults.
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Project description:Purpose:Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the literature. Studying the normal inter-patient kinetic variability may lead to other comparable studies to initiate more personalized therapies within the orthopedics. Methods:Trials are performed by 50 healthy young males who were not overweight and approximately of the same age and activity level. Spatial marker trajectories and ground reaction force registrations are imported into the Anybody Modeling System based on subject-specific geometry and the state-of-the-art TLEM 2.0 dataset. Hip and knee joint reaction forces were obtained by a simulation with an inverse dynamics approach. With these forces, a statistical model that accounts for inter-subject variability was created. For this, we applied a principal component analysis in order to enable variance decomposition. This way, noise can be rejected and we still contemplate all waveform data, instead of using deduced spatiotemporal parameters like peak flexion or stride length as done in many gait analyses. In addition, this current paper is, to the authors' knowledge, the first to investigate the generalization of a kinetic model data toward the population. Results:Average knee reaction forces range up to 7.16 times body weight for the forwarded leg during lunge. Conversely, during squat, the load is evenly distributed. For both motions, a reliable and compact statistical model was created. In the lunge model, the first 12 modes accounts for 95.26% of inter-individual population variance. For the maximal-depth squat, this was 95.69% for the first 14 modes. Model accuracies will increase when including more principal components. Conclusion:Our model design was proved to be compact, accurate, and reliable. For models aimed at populations covering descriptive studies, the sample size must be at least 50.
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