Consensus Head Acceleration Measurement Practices (CHAMP): Origins, methods, transparency and disclosure

The use of head kinematic measurement devices has recently proliferated owing to technology advances that make such measurement more feasible. In parallel, demand to understand the biomechanics of head impacts and injury in sports and the military has increased as the burden of such loading on the brain has received focused attention. As a result, the field has matured to the point of needing methodological guidelines to improve the rigor and consistency of research and reduce the risk of scientific bias. To this end, a diverse group of scientists undertook a comprehensive effort to define current best practices in head kinematic measurement, culminating in a series of manuscripts outlining consensus methodologies and companion summary statements. Summary statements were discussed, revised, and voted upon at the Consensus Head Acceleration Measurement Practices (CHAMP) Conference in March 2022. This manuscript summarizes the motivation and methods of the consensus process and introduces recommended reporting checklists to be used to increase transparency and rigor of future experimental design and publication of work in this field. The checklists provide an accessible means for researchers to apply the best practices summarized in the companion manuscripts when reporting studies utilizing head kinematic measurement in sport and military settings

Measuring Physical Demands in Basketball: An Explorative Systematic Review of Practices.

BACKGROUND:Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport. OBJECTIVES:The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term 'training load' to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature. METHODS:A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy. RESULTS:Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study. CONCLUSIONS:This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes

Workloads and injury risk in Premier League football

The English Premier League is faster and more intensive than ever, requiring an enhanced physical capacity from the players. In addition, the financial rewards for success have never been greater. This has increased the pressure on clubs to produce and develop talented players who can consistently perform under physical stress, whilst remaining injury free. To augment the chance of success, practitioners must prescribe workloads which stimulate positive adaptations, without unduly increasing injury risk. Therefore, the primary aim of this thesis was to understand the relationships between workload and injury in both youth and senior professional football. Chapter 2 investigated the validity, reliability and interchangeability of the systems used to measure workload in this thesis. Chapter 3 determined that the youth and senior squads have different training demands, and were therefore studied separately when identifying the workload-injury relationships. Chapters 4 (youth) & 5 (senior) explored the relative risks associated with given workloads. Both studies found that acute spikes in workload increased the risk of injury; however, this increase could be reduced with progressive increases in the chronic workload. The secondary aim of this thesis was then to determine the effectiveness of informed workload prescription as an injury prevention strategy. By applying the findings from the previous chapters into elite football practice, Chapter 6 found that appropriate workload prescription appears to increase workload tolerance, although it is not sensitive enough to be used as an isolated injury prevention tool

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

Advanced measurement for sports surface system behaviour under mechanical and player loading

This research project has investigated the mechanical behaviour of artificial turf surface systems used for sports under a range of real player movements, and the contribution of component layers to the overall system response by developing advanced measurement systems and methods. Artificial turf surface systems are comprised of a number of different materials and commonly with several layers, all of which contribute to their composite behaviour. During sports movements a player loads the surface, resulting in deformation that can change the surface behaviour, which in turn modifies the player biomechanical response. Improving the understanding of surface response to actual player loading is important for developing enhanced products for improving play performance. Likewise, by improving knowledge of surface effects on players, the understanding of injury risk can be improved. However, there is currently no published research to measure and analyse the behaviour of artificial turf system during real player locomotion. This research was undertaken to address this current lack of knowledge within the interaction between player and sports surface regarding the effects of player loading on the mechanical behaviour of artificial turf systems. In addition to support player loading regime, mechanical behaviour of hockey and third generation artificial turf surface systems and their component shockpad layers (a rubber shreds bonded shockpad and a polyurethane foam shockpad) was examined through dynamic cyclic compressive loading using an advanced material testing machine in laboratory environment. Each layer and carpet-shockpad system was subjected to controlled loading designed with previous biomechanical data at various loading frequencies (0.9 Hz, 3.3 Hz and 10 Hz) and under two different contact areas (50 mm and 125 mm diameter) to simulate aspects of player walking, running and sprinting. All layers and surface systems tested showed nonlinear stress-strain behaviour with hysteresis. Increasing the contact area resulted in reduced surface vertical deflection and more linear response. Increasing the loading frequency led to stiffer response in the lower stress range ( 600 kPa) and a decrease in maximum strain as the loading frequency increased. Hysteresis loops obtained at different loading frequencies indicated that the amount of energy lost at the same peak load of 1900 N in each surface system decreased with an increase in loading rate. Player loading regime was performed to quantify the load/stress and the resulting surface deformation/strain under subject loading. Measurement systems including motion capture system, force plate and high speed were developed to characterise the response behaviour in a novel way. The mechanical behaviour of artificial turf surface systems under three player movement patterns (heel-toe walking, forefoot running and forefoot single leg landing) was measured. Boot-surface contact area of each movement varied during the stance. The heel-toe walking results indicated that the maximum applied stress and surface strain occurred in very early stance (first 10%) when the boot-surface contact area was small. For forefoot running and landing, the peak surface strain occurred around mid-stance concurrent with the time of peak applied stress. The maximum strain measured under running was smaller than under landing. A thin-film pressure sensing mat was used in both mechanical and player loading regimes and proved to be a useful tool for evaluating the pressure distributions and contact areas at different interfaces of the surface system. The applied stress on surface was observed to greatly reduce with depth over increasing contact area through the surface systems. Although the average pressure was reduced, pressure distribution contour showed directly under the surface load area the pressure at depth was still relatively large and that outside of this area the pressure was much lower. A comparison of the mechanical behaviour of artificial turf systems in terms of compressive strain, modulus of elasticity, stress distribution and energy loss under mechanical and player loading was evaluated. Key loading parameters in different loading regimes and their influence on surface system response were determined. The structure and material intrinsic properties of shockpad were considered to further explain the observed surface system behaviour. Two mathematical models were used to fit through the experimental data and found to be able to describe the loading behaviour. A breakthrough in understanding of the effects of real player loading on the mechanical behaviour response of artificial turf systems, and the contribution of the components to the whole system response has been achieved through the development of advanced measurement techniques

Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with more than 1000 preprints related to NeRFs published. This paper serves as a bridge for people starting to study these fields by building on the basics of Mathematics, Geometry, Computer Vision, and Computer Graphics to the difficulties encountered in Implicit Representations at the intersection of all these disciplines. This survey provides the history of rendering, Implicit Learning, and NeRFs, the progression of research on NeRFs, and the potential applications and implications of NeRFs in today's world. In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation

Movement Characteristics of Front Crawl Swimming at Sprint Pace and Middle-Distance Pace: Establishing Demands on the Torso Muscles

Dry-land training of the torso muscles is common in swimming programs; however, the role of the torso muscles in front crawl is unclear. The purpose of this thesis was to establish demands on the torso muscles in front crawl from analysis of kinematic data and torso muscle activity during sprint and middle-distance swimming. In the first two studies, 3D kinematic data were analysed from swimmers swimming at sprint and 400m pace. In Study 1, the range of hip roll decreased while shoulder roll range was similar as swimming speed increased. These differences produced greater range and velocity of torso twist as swimming speed increased, indicating higher demands on the torso muscles at sprint than at 400m pace. In Study 2, Fourier analysis was used to decompose angular momentum signals to determine the impact of the flutter kick on longitudinal body rotation. The third harmonic frequency, representing effects from the flutter kick, was greater in lower limb than in upper limb angular momentum at both paces, indicating a reduction in the rotation transferred from the lower to upper limbs. This reduction was more pronounced at sprint than at 400m pace. In Study 3, 3D kinematic data and surface EMG data from internal oblique, external oblique, rectus abdominis, and lumbar and thoracic erector spinae were collected from swimmers swimming at sprint and 400m pace. Torso twist angle did not relate to EMG data and no relationships between muscle activity and torso twist acceleration could be detected. Findings from this study indicate that the torso muscles may play a greater role in stability and posture than they do in producing torso twist in front crawl. Guidelines were developed to improve dry-land training specificity for swimmers: (1) increase torso muscle demands as swimming speed increases, (2) use the torso muscles to provide stability during lower limbs movements, and (3) challenge the torso muscles to maintain torso posture while moving the upper and lower limbs

The BG News April 9, 2008

The BGSU campus student newspaper April 9, 2008. Volume 98 - Issue 136https://scholarworks.bgsu.edu/bg-news/8912/thumbnail.jp

Vision for Social Robots: Human Perception and Pose Estimation

In order to extract the underlying meaning from a scene captured from the surrounding world in a single still image, social robots will need to learn the human ability to detect different objects, understand their arrangement and relationships relative both to their own parts and to each other, and infer the dynamics under which they are evolving. Furthermore, they will need to develop and hold a notion of context to allow assigning different meanings (semantics) to the same visual configuration (syntax) of a scene. The underlying thread of this Thesis is the investigation of new ways for enabling interactions between social robots and humans, by advancing the visual perception capabilities of robots when they process images and videos in which humans are the main focus of attention. First, we analyze the general problem of scene understanding, as social robots moving through the world need to be able to interpret scenes without having been assigned a specific preset goal. Throughout this line of research, i) we observe that human actions and interactions which can be visually discriminated from an image follow a very heavy-tailed distribution; ii) we develop an algorithm that can obtain a spatial understanding of a scene by only using cues arising from the effect of perspective on a picture of a person’s face; and iii) we define a novel taxonomy of errors for the task of estimating the 2D body pose of people in images to better explain the behavior of algorithms and highlight their underlying causes of error. Second, we focus on the specific task of 3D human pose and motion estimation from monocular 2D images using weakly supervised training data, as accurately predicting human pose will open up the possibility of richer interactions between humans and social robots. We show that when 3D ground-truth data is only available in small quantities, or not at all, it is possible to leverage knowledge about the physical properties of the human body, along with additional constraints related to alternative types of supervisory signals, to learn models that can regress the full 3D pose of the human body and predict its motions from monocular 2D images. Taken in its entirety, the intent of this Thesis is to highlight the importance of, and provide novel methodologies for, social robots' ability to interpret their surrounding environment, learn in a way that is robust to low data availability, and generalize previously observed behaviors to unknown situations in a similar way to humans.</p