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A new method of data-domain full traveltime inversion (FTI) is proposed to estimate the near-surface velocity model using early arrivals in seismic shot gathers. Data-domain FTI is capable of generating a background velocity model from which the predicted early arrivals can kinematically match the observed ones. Such a match is measured and quantified in terms of the crosscorrelation function between the computed and observed traces. Our method aims to find an optimal estimated velocity model that minimizes the crosscorrelation computed from the selected early arrivals. The early arrivals are isolated via a sequence of operations, including the [Formula: see text]-[Formula: see text] scan, autopicking, multidomain quality control, and guide interpolation. Because windows, rather than exact arrival times, are constructed, the difficulties encountered while picking precise arrivals are reduced. In addition, the gradient of data-domain FTI is derived based on an amplitude-constrained optimization problem, which makes the gradient essentially different from that derived with the Born approximation in which no constraint is used. The constraint requires the inversion to honor traveltime information only, and it thus ignores any amplitude changes caused by velocity variations. This method is validated using 3D synthetic as well as field data sets. The results show that data-domain FTI, combined with the early arrival selection workflow, is able to generate reasonable background velocities that kinematically match the predicted early arrivals with the observed ones, and the associated depth-domain images are clearly improved.

資料番号: PA2020054000

Lossless data compression algorithms can use statistical redundancy to represent data using a fewer number of bits in comparison to the original uncompressed data. Run-Length Encoding (RLE) is one of the simplest lossless compression algorithms in terms of understanding its principles and software implementation, as well as in terms of temporal and spatial complexity. If this principle is applied to individual bits of original uncompressed data without respecting the byte boundaries, this approach is referred to as bit-level Run-Length Encoding. Lightweight algorithm for lossless data compression proposed in this paper optimizes bit-level RLE data compression, uses special encoding of repeating data blocks, and, if necessary, combines it with delta data transformation or representation of data in its original form intending to increase compression efficiency compared to a conventional bit-level RLE approach. The advantage of the algorithm proposed in this paper is in its low time and memory consumption which are basic features of RLE, along with the simultaneous increase of compression ratio, compared to the classical bit-level RLE approach.

Lossless data compression algorithms can use statistical redundancy to represent data using a fewer number of bits in comparison to the original uncompressed data. Run-Length Encoding (RLE) is one of the simplest lossless compression algorithms in terms of understanding its principles and software implementation, as well as in terms of temporal and spatial complexity. If this principle is applied to individual bits of original uncompressed data without respecting the byte boundaries, this approach is referred to as bit-level Run-Length Encoding. Lightweight algorithm for lossless data compression proposed in this paper optimizes bit-level RLE data compression, uses special encoding of repeating data blocks, and, if necessary, combines it with delta data transformation or representation of data in its original form intending to increase compression efficiency compared to a conventional bit-level RLE approach. The advantage of the algorithm proposed in this paper is in its low time and memory consumption which are basic features of RLE, along with the simultaneous increase of compression ratio, compared to the classical bit-level RLE approach.

We proposed a subaperture stitching method for concave–convex microstructured surfaces. The method is mainly based on wavelet transform (WT) and three-dimensional (3D) data matching. WT is applied to separate the high-frequency information from the low-frequency information, then the speeded-up robust feature-random sample consensus algorithm is used to match 3D surface data and calculate lateral displacement between adjacent subapertures. Finally, the pose is adjusted to obtain the stitching result. Simulations and experiments show that the proposed method can effectively stitch concave–convex microstructured surfaces.

The importance to learn disease progression patterns from longitudinal clinical data and use them effectively to improve prognosis, triggers the need for new approaches for three-way data analysis. In this context, triclustering has been widely researched for its potential in biomedical problems, showing promising results in the discovery of putative biological modules, patient profiles, and disease progression patterns. In this work, we propose a triclustering-based approach for three-way data classification, resulting from a combination of triclustering with random forests, and use it to predict the need for non-invasive ventilation in ALS patients. We analyse ALSFRS-R functional scores together with respiratory function tests collected from patient follow-up. The results are promising, enabling to understand the potential of triclustering and pinpointing improvements towards an effective triclustering-based classifier for clinical domains, taking advantage of the benefits of exploring disease progression patterns mined from three-way clinical data.

Regular monitoring is essential to understand coastal morphodynamics and anthropic as well as natural impacts, at different temporal and spatial scales. A stereoscopic video-based terrestrial mobil...

Three-dimensional data are increasingly prevalent across biomedical and social domains. Notable examples are gene-sample-time, individual-feature-time, or node-node-time data, generally referred to as observation-attribute-context data. The unsupervised analysis of three-dimensional data can be pursued to discover putative biological modules, disease progression profiles, and communities of individuals with coherent behavior, among other patterns of interest. It is thus key to enhance the understanding of complex biological, individual, and societal systems. In this context, although clustering can be applied to group observations, its relevance is limited since observations in three-dimensional data domains are typically only meaningfully correlated on subspaces of the overall space. Biclustering tackles this challenge but disregards the third dimension. In this scenario, triclustering—the discovery of coherent subspaces within three-dimensional data—has been largely researched to tackle these problems. Despite the diversity of contributions in this field, there still lacks a structured view on the major requirements of triclustering, desirable forms of homogeneity (including coherency, structure, quality, locality, and orthonormality criteria), and algorithmic approaches. This work formalizes the triclustering task and its scope, introduces a taxonomy to categorize the contributions in the field, provides a comprehensive comparison of state-of-the-art triclustering algorithms according to their behavior and output, and lists relevant real-world applications. Finally, it highlights challenges and opportunities to advance the field of triclustering and its applicability to complex three-dimensional data analysis.

We study some procedures for the approximation of three-dimensional data on a grid with a hypothesis of periodicity. The first part proposes a generalization of a discrete periodic approxim...

The article contains a comparative analysis of two methods of calculating angles in the shoulder joint of the right upper limb. For the purposes of this study, a marker-vector method was developed that calculates angles based on retroreflective 3D marker’s positions and vectors created on the basis of their positions. Movements from two types of sports (sword fighting and tennis forehand) were analysed. These movements were recorded using an optical motion capture system. The obtained results were compared with the values read from the Plug-in Gait biomechanical model from C3D files. The results show that the proposed method is more universal and can be used independently. In addition, the Plug-in Gait model is not adequate for the analysis of the acquired shoulder angles of tennis players.

In industrial production, the absence of clear component identification and unrecognized component defects can lead to a lack of protection against product piracy and unforeseen faults in machinery and equipment. In this context, data, which are stored directly in the subsurface region of a component ensuring its clear identification, as well as sensitive materials which act as sensors for high loading, can contribute to problem-oriented solutions. For robust, forgery-proof component identification that is inseparably linked to the component, three-dimensional data matrix codes are introduced into the component's subsurface region via a laser-induced local heat treatment. This technology ensures a sufficient data density. By locally tempering the metastable austenitic steel, areas are created where mechanical loads exceeding a defined level cause changes in the microstructure of the heat treated subsurface region. By means of adapting suitable read-out technologies, such as high-resolution eddy-current technology and the harmonic analysis of eddy-current signals, the data and load information stored in the component's subsurface region can be read non-destructively.

The recent prevalence of three dimensional (3D) images of soft and hard tissues provides a wealth of new data from which the clinician can evaluate these changes. However, evaluating this new data presents new and significant challenges. Current approaches utilizing multi-dimensional data for the precise evaluation of changes related to treatment and growth sets are reviewed. The results of current validation studies exploring approaches to these problems are reviewed, including the registration of longitudinal data using maxillary and mandibular regions of reference. Challenges related to the consistent selection of points on complex three-dimensional structures are circumvented using an automated, shape analysis based approach. Imaging using these new modalities yields a tremendous amount of data. Analysis of large data sets from cross-sectional studies with multiple variables are simplified using a principle components analysis, from which a reduced set of variables is constructed. Examples of this approach are presented. The use of advanced methods to process and interpret data from 3D imaging modalities highlights critical aspects of craniofacial growth and form.

Life structures is a basic part of therapeutic training as it is basic for the exact analysis in organs and human frameworks. The psychological portrayal of the shape and connection of various anatomical structures is a critical advance in the learning procedure. The motive behind this pilot study is to show the attainability and advantages of creating imaginative showing modules for life systems training of first-year restorative understudies dependent on 3D recreations from genuine patient information. The investigation on 3D model is creating and ended up being increasingly reasonable to the extent three dimensional data. The ascent of laser checks and impelled 3D instruments presented advance towards the quick improvement of any capricious model.

The article explores the possibilities of using convolutional neural networks to recognize the type of tennis shots. The study compares two architectures of such networks: Inception-v3 and MobileNet. Two datasets consisting of images of tennis players making an impact are analyzed in order to identify the type and phase of impact. The images in each of the collections were assigned to the respective five following classes: backhand preparation phase, backhand shot, forehand preparation phase, forehand shot and non-shot. In each of them there is a tennis player silhouette and a racket skeleton consisting of markers. Images of tennis players are generated from motion recordings made using motion capture technology. The networks were trained with different values of the learning rate. In addition, the network training time and match results for the best-trained models are presented. In view of the parameters considered, the MobileNet network has proved to be a better model.

Three dimensional data structures such as batch process data or infra-red spectral measurements usually contain inconsistent trajectories of various durations and quality. In the case of batch process data, most modeling methods require the data from all batches to be of same duration. For spectral data, peaks might be shifted from one sample to another due to unaccounted sources of variation. These inconsistencies are usually resolved through trajectory alignment (or synchronization) methods. In this paper, we first review the deficiencies of existing approaches. Next, a Constrained selective Derivative Dynamic Time Warping (CsDTW) method is proposed to perform automatic alignment of trajectories. Different from conventional methods, CsDTW preserves key features that characterizes the batch and only apply warping to regions of least impact to trajectory characterization. The proposed warping technique is applied to both industrial and simulated datasets to demonstrate its effectiveness.

Researchers disagree on the identity of dinosaurs that left footprints in the Lower Cretaceous Tetori Group of the Oshirakawa area (Japan). To clarify these identities, we quantitatively analyzed footprint data obtained from three-dimensional laser scanning technology. From these data, we identified six tracks belonging to dinosaurs. These six tracks were bipedal with a tridactyl morphology, which we could differentiate into large theropods (the ichnofamily Eubrontidae) and large ornithopods (similar to Amblydactylus-type). Our results indicate that the ichnofauna of the Oshirakawa site is richer than previously thought. Additionally, the cooccurrence of large theropod and Amblydactylus-type ornithopod footprints in the Oshirakawa area is the oldest in the Tetori Group (although a similar assemblage was identified in the Kitadani Formation, which is the uppermost part of the Tetori Group). Thus, quantitatively assessing dinosaur footprints using 3D digital data is an effective approach to identify dinosaur footprints.

We previously published a two-dimensional data-driven model (INSIM-FT) for history matching waterflooding production data and to identify flow barriers and regions of high connectivity between injector-producer pairs. This two-dimensional INSIM model assumed vertical wells. The history-matched models can be used for prediction of waterflooding performance and life-cycle waterflooding optimization. The INSIM-FT-3D model presented here extends INSIM-FT to three dimensions, considers gravity and enables the use of arbitrary well trajectories. INSIM-FT-3D places nodes at each well perforation and then adds nodes throughout the reservoir. Flow occurs through "streamtubes" between each pair of connected nodes. Mitchell's best candidate algorithm is used to place nodes and a three-dimensional (3D) connection map is generated with Delaunay triangulation. Pressures and saturations at nodes, respectively, are obtained from IMPES-like pressure equations and a Riemann solver that include gravity effects. With history-matched model(s) as the forward model(s), we estimate the optimal well controls (pressure or rates at control steps) that maximize the life-cycle net-present-value (NPV) of production under waterflooding using a gradient-based method that employs a stochastic gradient. Two 3D reservoirs are considered to establish the viability of using INSIM-FT-3D history-matched models for waterflooding optimization, a channelized reservoir and the Brugge reservoir. Unlike history-matching and waterflooding optimization based on reservoir simulation models, INSIM-FT-3D is not a detailed geological model. Moreover, the time required to run INSIM-FT-3D is more than one order of magnitude less the cost of running a comparable reservoir simulation model.

The rapid, efficient and non-destructive 3D morphological data acquisition of plants are great significance to the study of digital plant, functional structural plant model and crop phenotype. This paper discusses 3D data acquisition methods for smaller plant organs, which take maize grain as an example. Smartscan and Micro-CT scanning can be used to obtain the morphological data of the grains. The efficiency, accuracy, processing of data in two scanning ways are compared and analyzed. The results shows that the Micro-CT is more suitable for obtaining information of internal structure of maize grain. While grain morphology in SmartScan can get better visualization than Micro-CT, and the former one can also obtain image texture information. These two kinds of methods for volume measurement have good consistency except for Denghai 605. The study will provide theoretical basis for obtaining 3D data of plant organs at smaller scales.

Son yıllarda hızla ilerleyen dijital radyoloji teknolojisinin ürünü olan ve özellikle dentomaksillofasiyal yapıların görüntülenmesi amacıyla geliştirilen dental volumetrik tomografi (DVT), diş hekimliği uygulamalarında her geçen gün daha fazla kullanım alanı bulmaktadır. Medikal bilgisayarlı tomografi cihazlarına göre daha ucuz ve daha düşük radyasyon dozuna sahip olan DVT cihazları, diş hekimliğinde üç boyutlu verilerin elde edilmesine ve görüntüler üzerinde rekonstrüksiyon işlemlerinin yapılabilmesine olanak sağlamaktadır. Bu derlemede DVT görüntüleme sistemlerinin çalışma prensipleri, teknik özellikleri, kullanım alanları, avantaj ve dezavantajları ile ilgili genel bilgiler sunulmaktadır., Dental volumetric tomography (DVT), which is developed uniquely for dentomaxillofacial imaging, appeared in the dental world concurrently with recent rapid developments in digital radiology technology, and is becoming more popular in dental practice. DVT devices that generate lower radiation doses and have lower cost when compared to medical CT enable acquirement of three dimensional data and reconstruction of these digital images on personal computers. In this review, the principles, technical features, indications, advantages and disadvantages of DVT systems are presented.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Investigation of the performance of Dice (1945) measure of association when applied to three dimensional data. Variance for the measure is developed and examined. Comparison of the measure to Cohen's K (1960) and Yule's Y and Q (1900) is made across differing numbers of observation and locations of observations to evaluate measure performance. Diffusion tensor track images are used to examine the utility of agreement measures when comparing images. Goodman and Kruskal (1954) is used to identify utility of a common agreement/association measure.

Direct stem cell therapies for functionally impaired tissue require a sufficient number of cells in the target region and a method for verifying the fate of the cells in the subsequent time course. In vivo MRI of iron labeled mesenchymal stem cells has been suggested to comply with these requirements. The study was conducted to evaluate proliferation, migration, differentiation and adhesion effects as well as the obtained iron load of an iron labeling strategy for mesenchymal stem cells. After injection into the porcine urethral sphincter, the labeled cells were monitored for up to six months using MRI. Mesenchymal stem cells were labeled with ferucarbotran (60/100/200 µg/mL) and ferumoxide (200 µg/mL) for the analysis of migration and viability. Phantom MR measurements were made to evaluate effects of iron labeling. For short and long term studies, the iron labeled cells were injected into the porcine urethral sphincter and monitored by MRI. High resolution anatomical images of the porcine urethral sphincter were applied for detection of the iron particles with a turbo-spin-echo sequence and a gradient-echo sequence with multiple TE values. The MR images were then compared with histological staining. The analysis of cell function after iron labeling showed no effects on proliferation or differentiation of the cells. Although the adherence increases with higher iron dose, the ability to migrate decreases as a presumed effect of iron labeling. The iron labeled mesenchymal stem cells were detectable in vivo in MRI and histological staining even six months after injection. Labeling with iron particles and subsequent evaluation with highly resolved three dimensional data acquisition allows sensitive tracking of cells injected into the porcine urethral sphincter for several months without substantial biological effects on mesenchymal stem cells.

Additive manufacturing or 3D printing is the process by which three dimensional data fields are translated into real-life physical representations. 3D printers create physical printouts using heated plastics in a layered fashion resulting in a three-dimensional object. We present a technique for creating customised, inexpensive 3D orbit models for use in orbital surgical training using 3D printing technology. These models allow trainee surgeons to perform 'wet-lab' orbital decompressions and simulate upcoming surgeries on orbital models that replicate a patient's bony anatomy. We believe this represents an innovative training tool for the next generation of orbital surgeons.

Brain lesion segmentation is a critical application of computer vision to the biomedical image analysis. The difficulty is derived from the great variance between instances, and the high computational cost of processing three dimensional data. We introduce a neural network for brain tumor semantic segmentation that parses their internal structures and is capable of processing volumetric data from multiple MRI modalities simultaneously. As a result, the method is able to learn from small training datasets. We develop an architecture that has four parallel pathways with residual connections. It receives patches from images with different spatial resolutions and analyzes them independently. The results are then combined using fully-connected layers to obtain a semantic segmentation of the brain tumor. We evaluated our method using the 2017 BraTS Challenge dataset, reaching average dice coefficients of \(89\%\), \(88\%\) and \(86\%\) over the training, validation and test images, respectively.

Gas detection and identification is based on the spectral absorption peak feature, which is acquired by the spectrometer. FTIR imaging spectrometer has the advantages of high spectral resolution and good sensitivity, which are both suitable for the unknown or mixture gas identification applications, such as plume pollution monitoring, chemical agents detection and leakage detection. According to the application requirement, a dual band FTIR imaging spectrometer has been developed and verified. This FTIR imaging spectrometer combines the infrared thermal imaging sensor and Michelson interferometer to form the three dimensional data cube. Based on this instrument, the theoretical analysis and algorithm is introduced, and the numerical method is explained to illuminate the basic idea in gas identification based on spectral features. After that, the field verification test is setup and completed. Firstly, the FTIR imaging spectrometer is used to detect SF6, NH3 and the mixture gas, while the gas is exhausted out from the storage vase with a specific speed. Secondly, the instrument is delivered to the industrial area to monitor the plume emission, and analyze the components in plume. Finally, the instrument is utilized to monitoring the oil spill in ocean, and the practical maritime trial is realized. Further, the gas concentration evaluation method is discussed. Quantitative issue in gas identification is an important topic. The test results show that, based on the gas identification method introduced in this paper, FTIR imaging spectrometer can be utilized to identify the unknown gas or mixture gas in real time. The instrument will play a key role in environmental emergency and monitoring application.

The data presentation in digital archive is too complicated to understand for general tourists. Although tourists can easily acquire some information from digital archiving systems (DAS) through location-based services (LBS), they are unable to have an in-deep tour without understanding the data represented in three dimensions as time, space and topic. In recent years, spatial computing is proposed to transform the use of DAS from location-aware into location-understanding. Unfortunately, the application programming interface (API) of most DAS is not intuitive and inefficient to query the data stored in DAS. In this paper, we will present a three-dimensional data query system (3DQS) using the proposed API proxy mechanism. The contributions of proposed 3DQS include (1) providing a friendly API to query three-dimensional data in DAS, (2) caching data being requested, and (3) prefetching data according to the time, space, and topic localities predicted from users’ interests.

The forehand is one of the key shot in tennis. Its reparability is a very important aspect of gaining points. The first purpose of this paper is to create the algorithms for calculating the motion parameters for the preparation phase of the forehand, such as: the position of the head of the tennis racket relative to the player’s body, the elbow angle (i.e. whether the arm is bent or straight) and the placement of the player’s feet towards the front of the pelvis. The second aim of the study is to calculate the repeatability of the selected motion parameters (both for the body and the racket) of the preparation phase of the tennis forehand using coefficient of variation. The shots were performed in the motion capture laboratory using the Plug-in Gait biomechanical model. The described parameters are computed from three dimensional data, stored in C3D file.

This study strives to analyze the characteristics of and changes in breast shapes of women in their 30s, whose bodies start to age and whose breasts experience changes due to internal and external factors such as pregnancy, childbearing, and breast-feeding. The analysis of the indirect breast measurements for each age group (early, mid, and late 30s) demonstrates that the volume of the breasts increases proportionally with age, the breasts lose their firmness, and the nipples start to point downwards rather than to the sides. The breast shapes experience more significant changes vertically than horizontally as the breasts start to sag downwards. The composition factors of the breasts have been classified into five factors: the level of volume in the breasts and the surrounding area, the degree of sagging in the breasts, the position and vertical width of the breasts, the volume of the breasts, and the degree of width between the breasts. The breasts have been categorized into three different shapes. Breast Shape I (32.56%) appeared most frequently among women in their mid 30s, and this shape falls into the category of Sagging I, which is one of the six breast types that have been classified by the Japanese Wacoal Research Center, in addition to Korean size 80A. Breast Shape II (38.76%) appeared most frequently among women in their mid 30s, and this shape has been categorized as flat with its size being 70A. Breast Shape III (28.68%) appeared most frequently among women in their early 30s with a conical shape and size 75A.

Three-dimensional data arrays (collections of individual data matrices) are increasingly prevalent in modern data and pose unique challenges to pattern extraction and visualization. This article introduces a biclustering technique for exploration and pattern detection in such complex structured data. The proposed framework couples the popular plaid model together with tools from functional data analysis to guide the estimation of bicluster responses over the array. We present an efficient algorithm that first detects biclusters that exhibit strong deviations for some data matrices, and then estimates their responses over the entire data array. Altogether, the framework is useful to home in on and display underlying structure and its evolution over conditions/time. The methods are scalable to large datasets, and can accommodate a variety of dynamic patterns. The proposed techniques are illustrated on gene expression data and bilateral trade networks. Supplementary materials are available online.

Reverse engineering and spatial digitization became more popular recently. The popularity grows with the devices which are capable to scan the human figures, cars, parts of the buildings or even bigger objects in a single process. In general, scanning devices sometimes present disproportionate costs as the usual additional software often tops the half of the hardware price. Text of this paper is focused on the alternative device which can use very affordable software applications to generate the same results as the most expensive scanning equipment. Particular parts of this article briefly describe the principles of non-contact three dimensional scanning using the Kinect device, the process of data processing in alternative software applications and possibilities of their further utilization.

3D Laser scanning technology gained more and more importance for the recording and documentation of architectural heritage. Especially for the survey of heterogeneous surfaces and complex structures it is a fast and reliable option for survey and so appreciated sources for research in architecture. Therefore the integration of laser scanning as a part of the building survey became a kind of standard procedure for objects of different scale, shape, age and origin. In some cases more than one team records an object with different devices using altering approaches. For example a client provides existing data from a part of the object that can't be accessed anymore, but is important to be integrated into the overall survey. The merging of the datasets may become challenging, especially if one survey is not documented in detail, in particular when it comes to the quality of the result. For a research about the traditional architecture of Saudi Arabia a building in the historic part of Jeddah has been surveyed in detail by a team of researchers of the Vienna University of Technology. Within this frame a workshop for students of the King Abdul Aziz about building archaeological research has been conducted. As part of the results consists of two sets of laserscan data, recorded with different laser scanners. Using these data a possible approach for the registration of scan data from different and/or unknown provenance has been developed which will be outlined in this paper.

1: Here we describe a novel design to obtain three dimensional data on the movements of aquatic organisms at depths of up to 140 meters. 2: The setup consists of two synchronized high-speed cameras fixed to two articulated arms. 3: The setup was successfully used to film and quantify the locomotion of coelacanths (Latimeria chalumnae) living at a depth of about 120 meters in Sodwana Bay, South Africa. As an example, the detailed motion of the dorsal fin is presented here. 4: This setup can be used for any underwater applications that require synchronized video recordings of medium to large sized animals. This article is protected by copyright. All rights reserved.

The aim of the article is to present a model of the rower, taking into account the most important angles and the new algorithms for studying the position of the rower’s body at different phases of rowing. The positions of the rower’s back, elbows and wrists during rowing were analyzed. The paper presents research on the motion capture of rowers practicing on the Concept II Indoor Rower ergometer, using a motion capture system produced by Vicon. The data obtained with the motion capture system and the results generated with the proposed algorithm(s) allow to clearly identify the studied subjects’ degree of training and rowing technique on the basis of the analysis of changes in the inclination of the body parts in different phases of rowing.

The formation of three-dimensional data sets and the extraction of horizontal or quasi-horizontal time slices from these are described and discussed, including the effects of variable transmission velocity. A short calculation of the potential depth distortion is included for the reader to try. Data contouring and amplitude mapping are also described.

Mechanical simulators are used to simplify the human kicking motion to provide repeatable contact between the endeffector and ball. The aim of the study was to examine the feasibility of using an ankle joint capable of simulating the plantar flexion deformation mechanism experienced by the human foot during the interaction with the soccer ball. A foot geometry was used to allow soccer boots to be fitted to the end-effector with a semi-bonded bush bearing to act as the ankle joint. The bearing provides a torsional resistance to radial loading, returning the foot to its starting position after the foot and ball impact. High speed video analysis using the GOM PONTOS system created three dimensional data points from markers placed on the end-effector, resulting in the relative rotations being quantified. Similarities between the plantar flexion mechanism in human kicking and the end-effector were observed, with a greater magnitude experienced by the end-effector. The end-effector provided repeatable foot rotations when struck with different initial foot velocities. The study concluded that a semi-bonded bush bearing can be used as an ankle joint to create repeatable contact between a foot geometry and a soccer ball. By increasing the bearing stiffness, the plantar flexion angular displacement can be reduced to levels experienced in human kicking.