Patients with hallux valgus are known to alter lower limb joint kinematics during gait. However, little information is available about gait changes following hallux valgus surgery. We aimed to ...longitudinally investigate lower limb kinematic changes at the mid and terminal stances of gait after hallux valgus surgery.
This prospective observational study included 11 female patients (17 feet), who underwent first metatarsal osteotomy. Gait analyses were performed preoperatively and 1- and 2-year postoperatively using a three-dimensional motion capture system. Toe-out angle, ankle, knee, and hip joint angles during gait were calculated from the recorded data. The spatiotemporal parameters and these angles at the mid and terminal stances of gait were statistically compared between preoperative and postoperative periods.
All spatiotemporal parameters remained unchanged postoperatively. The toe-out angle was significantly greater at 1- and 2-year postoperatively. The ankle pronation angle, the knee abduction angle, and the hip adduction angle at the mid and terminal stances of gait were smaller postoperatively compared to the preoperative. These angular changes showed a similar trend at 1 and 2 years postoperatively. However, the postoperative changes of the sagittal joint angles were relatively small.
Hallux valgus surgery can affect the toe-out angle and the lower limb coronal kinematics at the mid and terminal stances of gait in patients with hallux valgus. However, surgical correction of hallux valgus deformity did not directly improve the gait characteristics in patients with hallux valgus.
•Kinematic effects of ankle, knee, and hip joints during gait in bunion surgery.•Preoperative and 1- and 2-year postoperative gait analyses by a motion capture system.•Bunion surgery changes toe-out angle and lower limb coronal kinematics during gait.
This paper proposes a novel algorithm for multiview stereopsis that outputs a dense set of small rectangular patches covering the surfaces visible in the images. Stereopsis is implemented as a match, ...expand, and filter procedure, starting from a sparse set of matched keypoints, and repeatedly expanding these before using visibility constraints to filter away false matches. The keys to the performance of the proposed algorithm are effective techniques for enforcing local photometric consistency and global visibility constraints. Simple but effective methods are also proposed to turn the resulting patch model into a mesh which can be further refined by an algorithm that enforces both photometric consistency and regularization constraints. The proposed approach automatically detects and discards outliers and obstacles and does not require any initialization in the form of a visual hull, a bounding box, or valid depth ranges. We have tested our algorithm on various data sets including objects with fine surface details, deep concavities, and thin structures, outdoor scenes observed from a restricted set of viewpoints, and "crowded" scenes where moving obstacles appear in front of a static structure of interest. A quantitative evaluation on the Middlebury benchmark 1 shows that the proposed method outperforms all others submitted so far for four out of the six data sets.
Biomechanical evaluations of sport-specific jump-landing tasks may provide a more ecologically valid interpretation compared to generic jump-landing tasks. For accurate interpretation of longitudinal ...research, it is essential to understand the reliability of biomechanical parameters of sport-specific jump-landing tasks.
How reliable are hip, knee and ankle joint angles and moment curves during two volleyball-specific jump-landing tasks and is this comparable with the reliability of a generic jump-landing task?
Three-dimensional (3D) biomechanical analyses of 27 male volleyball players were performed in two sessions separated by one week. Test-retest reliability was analyzed by calculating integrated as well as 1D intraclass correlation coefficient (ICC) and integrated standard error of measurement (SEM) for hip, knee and ankle angles and moments during a spike and block jump (volleyball-specific tasks), and during a drop vertical jump (generic task).
Reliability of joint angles of volleyball-specific and generic jump-landing tasks are similar with excellent-to-good integrated ICC for hip, knee and ankle flexion/extension (ICC= 0.61–0.89) and hip and knee abduction/adduction (ICC=0.61–0.78) but fair-to-poor ICC for ankle abduction/adduction (ICC=0.28–0.52) and hip, knee and ankle internal/external rotation (ICC=0.29–0.53). Reliability of hip, knee and ankle joint moments was good-to excellent (ICC= 0.62–0.86) except for hip flexion moment during spike jump and drop vertical jump (ICC=0.43–0.47) and knee flexion moment during both volleyball-specific tasks (ICC=0.56–0.57). For all tasks, curve analysis revealed poorer reliability at start and end of the landing phase than during the midpart.
Our data suggests that kinematic evaluations of volleyball-specific jump-landing tasks are reliable to use in screening programs, especially in the sagittal plane. Notably, reliability is poorer at the beginning and end of the landing phase, requiring careful interpretation. In conclusion, the results of this study indicate the potential for integration of sport-specific jump-landing tasks in screening programs, which will be more ecologically valid.
•Kinematics and kinetics of volleyball-specific and generic landing tasks are similar reliable.•Ankle frontal plane and transversal plane angles of all joints are poor reliable.•Start and end of the landing phase are poorer reliable than the midpart.•Biomechanical analysis of sport-specific tasks could be used in screening programs.
Shoulder instability (SI) is a complex impairment, and identifying biomarkers that differentiate subgroups is challenging. Children and adolescents with SI (irrespective of etiology) have differences ...in their movement and muscle activity profiles compared to age- and sex-matched controls (2-tailed). There are limited fundamental movement and muscle activity data for identifying different mechanisms for SI in children and adolescents that can inform subgrouping and treatment allocation.
Young people between 8 and 18 years were recruited into 2 groups of SI and age- and sex-matched controls (CG). All forms of SI were included, and young people with coexisting neurologic pathologies or deficits were excluded. Participants attended a single session and carried out 4 unweighted and 3 weighted tasks in which their movements and muscle activity was measured using 3-dimensional (3D) movement analysis and surface electromyography (sEMG). Statistical parametric mapping was used to identify between-group differences.
Data were collected for 30 young people (15 SI 6 male, 9 female and 15 CG 8 male, 7 female). The mean (standard deviation) age of the participants was 13.6 years (3.0). The SI group demonstrated consistently more protracted and elevated sternoclavicular joint positions during all movements. Normalized muscle activity in latissimus dorsi was lower in the SI group and had the most statistically significant differences across all movements. Where differences were identified, the SI group also had increased normalized activity of their middle trapezius, posterior deltoid, and biceps muscles but decreased activity of their latissimus dorsi, triceps and anterior deltoid muscles compared with the CG group. No statistically significant differences were found for the pectoralis major across any movements. Weighted tasks produced fewer differences in muscle activity patterns compared with unweighted tasks.
Young people with SI may adapt their movements to minimize glenohumeral joint instability. This was demonstrated by reduced variability in acromioclavicular and sternoclavicular joint angles, adoption of different movement strategies across the same joints, and increased activity of the scapular stabilizing muscles, despite achieving similar arm positions to the CG. Young people with SI demonstrated consistent differences in their muscle activity and movement patterns. Consistently observed differences at the shoulder girdle included increased sternoclavicular protraction and elevation accompanied by increased normalized activity of the posterior scapula–stabilizing muscles. Existing methods of measurement may be used to inform clinical decision making; however, further work is needed to evaluate the prognostic and clinical utility of derived 3D and sEMG data for informing decision making within SI.
A membrane‐receptor‐analysis method termed ligand dilution analysis, which combines the concepts of single‐molecule localization and random sampling, is reported by Yifan Lyu, Jianhui Jiang, Weihong ...Tan et al. in their Research Article (e202215387). Aptamer binding characterization, including receptor density calculation, single‐molecule colocalization, binding site determination, motion and fluctuation analysis, was performed with minimal probe and instrument requirements.
•Review of the recent literature in 3D human pose estimation from RGB images and videos.•Release of a challenging, publicly available, 3D pose estimation synthetic dataset.•Extensive experimental ...evaluation of some representative state-of-the-art methods.
Estimating the pose of a human in 3D given an image or a video has recently received significant attention from the scientific community. The main reasons for this trend are the ever increasing new range of applications (e.g., human-robot interaction, gaming, sports performance analysis) which are driven by current technological advances. Although recent approaches have dealt with several challenges and have reported remarkable results, 3D pose estimation remains a largely unsolved problem because real-life applications impose several challenges which are not fully addressed by existing methods. For example, estimating the 3D pose of multiple people in an outdoor environment remains a largely unsolved problem. In this paper, we review the recent advances in 3D human pose estimation from RGB images or image sequences. We propose a taxonomy of the approaches based on the input (e.g., single image or video, monocular or multi-view) and in each case we categorize the methods according to their key characteristics. To provide an overview of the current capabilities, we conducted an extensive experimental evaluation of state-of-the-art approaches in a synthetic dataset created specifically for this task, which along with its ground truth is made publicly available for research purposes. Finally, we provide an in-depth discussion of the insights obtained from reviewing the literature and the results of our experiments. Future directions and challenges are identified.
This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at ...the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo-code and the parameter values used) and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate. We also analyze the performance of a downscaled version of our algorithm to the absolute minimum of one comparison and one byte of memory per pixel. It appears that even such a simplified version of our algorithm performs better than mainstream techniques.
Detecting coherent groups is fundamentally important for crowd behavior analysis. In the past few decades, plenty of works have been conducted on this topic, but most of them have limitations due to ...the insufficient utilization of crowd properties and the arbitrary processing of individuals. In this study, a Multiview-based Parameter Free framework (MPF) is proposed. Based on the L1-norm and L2-norm, we design two versions of the multiview clustering method, which is the main part of the proposed framework. This paper presents the contributions on three aspects: (1) a new structural context descriptor is designed to characterize the structural properties of individuals in crowd scenes; (2) a self-weighted multiview clustering method is proposed to cluster feature points by incorporating their orientation and context similarities; and (3) a novel framework is introduced for group detection, which is able to determine the group number automatically without any parameter or threshold to be tuned. The effectiveness of the proposed framework is evaluated on real-world crowd videos, and the experimental results show its promising performance on group detection. In addition, the proposed multiview clustering method is also evaluated on a synthetic dataset and several standard benchmarks, and its superiority over the state-of-the-art competitors is demonstrated.
In this paper, we present a novel end-effector (payload) motion-based control development approach for the regulation of underactuated overhead cranes, which is efficient even in the presence of ...external disturbance and system parameter variations/uncertainties. The control system is elegantly constructed so that the problem of simultaneously regulating the trolley motion and suppressing the payload swing is successfully addressed by stabilizing a newly defined payload motion signal. Specifically, we first couple the actuated trolley motion and the unactuated payload swing via the defined payload motion signal, based on which a new energy storage function is established. Consequently, a payload motion-based control law is constructed straightforwardly, and the equilibrium point of the resulting closed-loop system is proven to be asymptotically stable by Lyapunov techniques and LaSalle's invariance theorem. Unlike traditional energy-based controllers, the proposed control law takes a much simpler structure independent of the system parameters. Both simulation and experimental results are included to demonstrate the superior performance of the proposed control method over some traditional controllers and its robustness against parameter variations, which illuminates the promising practical application potentiality of the designed crane control system.
Researchers face the challenge of defining subject selection criteria when training algorithms for human activity recognition tasks. The ongoing uncertainty revolves around which characteristics ...should be considered to ensure algorithmic robustness across diverse populations. This study aims to address this challenge by conducting an analysis of heterogeneity in the training data to assess the impact of physical characteristics and soft-biometric attributes on activity recognition performance.
The performance of various state-of-the-art deep neural network architectures (tCNN, hybrid-LSTM, Transformer model) processing time-series data using the IntelliRehab (IRDS) dataset was evaluated. By intentionally introducing bias into the training data based on human characteristics, the objective is to identify the characteristics that influence algorithms in motion analysis.
Experimental findings reveal that the CNN-LSTM model achieved the highest accuracy, reaching 88%. Moreover, models trained on heterogeneous distributions of disability attributes exhibited notably higher accuracy, reaching 51%, compared to those not considering such factors, which scored an average of 33%. These evaluations underscore the significant influence of subjects’ characteristics on activity recognition performance, providing valuable insights into the algorithm’s robustness across diverse populations.
This study represents a significant step forward in promoting fairness and trustworthiness in artificial intelligence by quantifying representation bias in multi-channel time-series activity recognition data within the healthcare domain.
•Systems have emerged that provide real-time feedback on patient performance.•Bias in human activity models for healthcare applications must be investigated.•Equity and fairness must be ensured in AI models that impact human safety and health.
PDF
