Wide area detection system: Conceptual design study

An integrated sensor for traffic surveillance on mainline sections of urban freeways is described. Applicable imaging and processor technology is surveyed and the functional requirements for the sensors and the conceptual design of the breadboard sensors are given. Parameters measured by the sensors include lane density, speed, and volume. The freeway image is also used for incident diagnosis

Non-contact measures to monitor hand movement of people with rheumatoid arthritis using a monocular RGB camera

Hand movements play an essential role in a person’s ability to interact with the environment. In hand biomechanics, the range of joint motion is a crucial metric to quantify changes due to degenerative pathologies, such as rheumatoid arthritis (RA). RA is a chronic condition where the immune system mistakenly attacks the joints, particularly those in the hands. Optoelectronic motion capture systems are gold-standard tools to quantify changes but are challenging to adopt outside laboratory settings. Deep learning executed on standard video data can capture RA participants in their natural environments, potentially supporting objectivity in remote consultation. The three main research aims in this thesis were 1) to assess the extent to which current deep learning architectures, which have been validated for quantifying motion of other body segments, can be applied to hand kinematics using monocular RGB cameras, 2) to localise where in videos the hand motions of interest are to be found, 3) to assess the validity of 1) and 2) to determine disease status in RA. First, hand kinematics for twelve healthy participants, captured with OpenPose were benchmarked against those captured using an optoelectronic system, showing acceptable instrument errors below 10°. Then, a gesture classifier was tested to segment video recordings of twenty-two healthy participants, achieving an accuracy of 93.5%. Finally, OpenPose and the classifier were applied to videos of RA participants performing hand exercises to determine disease status. The inferred disease activity exhibited agreement with the in-person ground truth in nine out of ten instances, outperforming virtual consultations, which agreed only six times out of ten. These results demonstrate that this approach is more effective than estimated disease activity performed by human experts during video consultations. The end goal sets the foundation for a tool that RA participants can use to observe their disease activity from their home.Open Acces

Evaluating the reliability of four-dimensional computed tomography scans of the wrist

Introduction: Four-dimensional CT (or 4D CT) scans are a novel approach to diagnosing musculoskeletal pathology. Although still in its infancy, there has been a surge of interest in identifying clinical applications for musculoskeletal 4D CT. The scapholunate joint has received the most attention thus far due to the complex articulations and challenges faced with prompt diagnosis of scapholunate injuries. The objective of this thesis is to review current literature on musculoskeletal 4D CT and to evaluate the inter- and intra-rater reliability of the assessment of scapholunate stability in 4D CT wrist scans. Methodology: 4D CT scans of thirteen healthy volunteers and four patients were prepared. Seven orthopaedic and plastic surgeons were recruited to qualitatively assess the stability of the scapholunate joint in the 4D CT scans. Statistical analysis included percent agreement, Fleiss’ kappa, and Gwet’s AC1 coefficient. Results: The percent agreement amongst all raters was 0.80392 (95% CI: 0.675 - 0.932). Fleiss’ Kappa was 0.54895 (95% CI: 0.252 - 0.846) and Gwet’s AC₁ was 0.54895 (95% CI: 0.391 - 0.915). The intraclass correlation coefficient (ICC) for intra-rater reliability was 0.71631 (95% CI: 0.5567 – 0.8423). Conclusion: Our pilot study suggests good inter- and intra-rater reliability for the qualitative assessment of scapholunate instability in 4D CT scans. Although further studies are required, this thesis highlights the vast potential of 4D CT as a non-invasive diagnostic technique of dynamic musculoskeletal injuries

Designing a Contactless, AI System to Measure the Human Body using a Single Camera for the Clothing and Fashion Industry

Using a single RGB camera to obtain accurate body dimensions rather than measuring these manually or via more complex multi-camera or more expensive 3D scanners, has a high application potential for the apparel industry. In this thesis, a system that estimates upper human body measurements using a set of computer vision and machine learning techniques. The main steps involve: (1) using a portable camera; (2) improving image quality; (3) isolating the human body from the surrounding environment; (4) performing a calibration step; (5) extracting body features from the image; (6) indicating markers on the image; (7) producing refined final results. In this research, a unique geometric shape is favored, namely the ellipse, to approximate human body main cross sections. We focus on the upper body horizontal slices (i.e. from head to hips) which, we show, can be well represented by varying an ellipse’s eccentricity, this per individual. Then, evaluating each fitted ellipse’s perimeter allows us to obtain better results than the current state-of-the-art for use in the fashion and online retail industry. In our study, I selected a set of two equations, out of many other possible choices, to best estimate upper human body horizontal cross sections via perimeters of fitted ellipses. In this study, I experimented with the system on a diverse sample of 78 participants. The results for the upper human body measurements in comparison to the traditional manual method of tape measurements, when used as a reference, show ±1cm average differences, sufficient for many applications, including online retail

An Applied Approach to Attacking Effectiveness in Professional Football

With ever growing financial invest in elite (association) football (soccer), it becomes increasingly more important to operate at the highest possible standard. A stable football organisation allows for more long-term success and greater investments. With this, objective and thorough analyses of the work done and future requirements become irreplaceable. This in turn opens the door for the instalment or development of analysis departments and analyst positions within elite football teams. These analysts, usually coming from a scientific background, rely on accurate and reliable data. The quality of the analyses, or analysts for that matter, then depends on the work done and choices made. The current research programme was designed to guide practitioners to effectively analyse and apply the data currently collected in elite football. Because match analysis in football has come a long way since first mentioned in a scientific journal in 1968. From basic notational metrics collected live during matches, through comprehensively studying video footage and having computers take over the collection of match parameters altogether. Currently, no matter whether positional time-motion data, metrics describing all on-the-ball match events or computerised combinations of the two are taken into consideration, the possibilities are seemingly endless. That means, analysts should be aware of the context of the data in order to appropriately interpret the results. Generally speaking, the focus and goals of the analyses should be clear and that is where this research programme started off. In many elite sports, like football, being successful depends on winning. Whether this is a short-term requirement or is treated as a long-term process with potential setbacks anticipated, is a decision made by clubs and directors. On the field, where the coach is responsible and analysts often support decision making, success often depends on scoring goals. Regardless of the fact one wants to score more or concede less than the opponent, at least one goal is required to win. That is why the current research programme acknowledged a goal to be the most decisive event in elite football. With that notion in mind, multiple studies were designed to answer the question of how teams can become more effective in scoring goals. The first study was designed to determine the differences between shots that led to a goal and shots that did not. This was done by studying attempts made from statistically identical locations on the pitch, however with changing situational circumstances (context). It was found that the magnitude of effect of opponent positioning changed for different shooting locations and offensive players. The results showed that the selected contextual factors were not able to explain all variance in shooting outcome, however that they should be kept in mind whilst analysing match events. Generally, since opponent presence and pressure were found to influence some shots, the notion that time (e.g. space) is of importance during an attacking sequence came to light. How and when this space between opposing players came to be, was studied in the second investigation of the current programme. Since (theoretically) balance exists between both teams of eleven players, a perturbation of this balance needs to occur prior to a goal scoring opportunity. Expert observers qualitatively analysed a series of match events between elite teams from ball recovery to the moment of the shot. Specific playing styles or actions were not identified to disturb a team's balance; however, agreement was found for a timepoint approximately five seconds prior to the shot to be most detrimental. Furthermore, experts showed stronger agreements when a sequence led to a goal, although they were unaware of the outcome. This importance of a strong perturbation, highlighted, again, the significance of sufficient space for an attacker to release a threatening shot. Finally, also since the balance was disturbed some time before the shot, there seems to be more at hand during a successful attack than a simply well-executed shot. After validating a low-cost tracking system in the third study, so this could be used in a sub-elite environment with a team willing to share full time-motion and tactical data, the final, fourth, study was designed. Here, physical parameters prior to shooting attempts were compared for different outcomes. It was found that an increased physical output, describing both the covered distance and intensity of movements, and fewer defenders behind the ball related to greater attacking success. Similarly, when defenders had to cover more distance prior to a shot, the chances of conceding a goal increased too. Together with a noteworthy relationship between lower match output and both attacking as well as defensive success, the importance of creating space or covering opponents were highlighted once more. Conclusively, by taking football's most decisive event, a goal, into account, the understanding of how to play more effectively has considerably grown. At the same time, the current research programme showed how analysts could effectively apply commonly collected match data into day-to-day practice. By identifying and acknowledging the context during crucial events, more information towards improved decision making and player profiling may be gathered. Future scientific studies may take this applied approach as a guideline for worthwhile large-scale solutions. With machines capable of learning along the way and taking comprehensive datasets into account, the potential for match analysts is substantial. With science supporting practitioners to answer the questions asked by coached and directors, financial investments in both fields may follow and allow for a bright future

SANE (Easy Gait Analysis System): Towards an AI-Assisted Automatic Gait-Analysis

The gait cycle of humans may be influenced by a range of variables, including neurological, orthopedic, and pathological conditions. Thus, gait analysis has a broad variety of applications, including the diagnosis of neurological disorders, the study of disease development, the assessment of the efficacy of a treatment, postural correction, and the evaluation and enhancement of sport performances. While the introduction of new technologies has resulted in substantial advancements, these systems continue to struggle to achieve a right balance between cost, analytical accuracy, speed, and convenience. The target is to provide low-cost support to those with motor impairments in order to improve their quality of life. The article provides a novel automated approach for motion characterization that makes use of artificial intelligence to perform real-time analysis, complete automation, and non-invasive, markerless analysis. This automated procedure enables rapid diagnosis and prevents human mistakes. The gait metrics obtained by the two motion tracking systems were compared to show the effectiveness of the proposed methodology

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts

Traumatic anterior shoulder dislocation:What is required to define optimal treatment strategies?

Traumatic anterior shoulder, or glenohumeral, dislocations are painful and functional shoulder instability limits patients in performing activities of daily living, sports and work. Up to 60% of patients experience redislocation following a first-time dislocation. If a patient experiences redislocation, it can increase damage to the joint, which in turn is associated with a higher redislocation risk. Selecting optimal treatment for patients can be a challenging process. There are effective operative interventions available, but it is unclear which patients should receive which intervention and in which stage. Risk factors associated with redislocation or worse outcomes can identify which treatment is suitable for the patient. These factors can guide the shared-decision making process when specific risk factors can be managed with the intervention of interest. This thesis demonstrates that (1) there are many inconsistencies in selection and definitions of risk factors; (2) the predictive value of risk factors can differ in specific patient groups; (3) it is important to evaluate the reliability and accuracy of quantifiable risk factors; (4) 3D position of the bony structures relative to each other can be a potential risk factor for redislocation; (5) there is insufficient awareness for standardization, timing and reporting of patient-reported outcome measures and (6) healthcare providers and patients can reach a consensus on which items are considered important to evaluate in shoulder instability research. Finally, taking these conclusions into account, it discusses what is required to define optimal treatment strategies following traumatic anterior shoulder dislocation