Background:Obesity and overweight are commonplace, yet attrition rates in weight management clinics are high. Traditional methods of body measurement may be a deterrent due to invasive and time-consuming measurements and negative experiences of how data are presented back to individuals. Emerging new technologies, such as three-dimensional (3D) surface imaging technology, might provide a suitable alternative. This study aimed to understand acceptability of traditional and 3D surface imaging-based body measures, and whether perceptions differ between population groups.Methods:This study used a questionnaire to explore body image, body measurement and shape, followed by a qualitative semi-structured interview and first-hand experience of traditional and 3D surface imaging-based body measures.Results:49 participants responded to the questionnaire and 26 participants attended for the body measurements and interview over a 2-month period. There were 3 main themes from the qualitative data 1) Use of technology, 2) Participant experience, expectations and perceptions and 3) Perceived benefits and uses.Conclusion:From this study, 3D-surface imaging appeared to be acceptable to patients as a method for anthropometric measurements, which may reduce anxiety and improve attrition rates in some populations. Further work is required to understand the scalability, and the role and implications of these technologies in weight management practice. (University Research Ethics Committee reference number ER41719941).

Investigations of elite tennis match-play have highlighted the importance of serving and returning strategies. This study establishes the most common and effective strategies used by male and female players at Wimbledon, and identifies associated winner-loser differences. Hawk-Eye ball-tracking data from 302 men's and 139 women's singles matches contested between 2016 and 2018 were analysed using confidence intervals, Chi-square and Chi-square partitions. For both sexes, first serves to lateral areas (Zones A and D) of the service boxes were more common and more successful than first serves to central areas (Zones B and C). Second serves to lateral areas also tended to be more successful than those to central areas, but players typically prioritised safety, often executing second serves to Zone C (central, but towards the backhand of right-handed opponents). Men and women hit more serve-returns to central areas than lateral areas of the court, despite serve-returns to lateral areas being more successful. Furthermore, winning male players were more accurate than losing male players, executing a comparatively higher percentage of serves and returns to lateral areas; winning female players demonstrated this on first serves only. These findings can be used to improve the specificity and representativeness of players' grass court training.

Notational analysis investigations of several sports have suggested that the performance characteristics associated with success differ by match closeness. It is not known whether this is the case in tennis. Therefore, this study aimed to first develop operational definitions for closely contested and one-sided tennis matches, then establish whether the important performance characteristics in elite grass court tennis differ by match closeness. Data from 365 men and 374 women's Wimbledon single matches played between 2015 and 2017 were analyzed. Irrespective of match closeness, points won of 0-4 shot rally length, first serve points won and baseline points won were associated with winning matches, and forced errors and unforced errors were associated with losing matches, for both sexes. Spearman's rank-order correlations demonstrated excellent agreement between the importance of the performance characteristics in closely contested and one-sided men (r(s) = 0.89, p < 0.001) and women's matches (r(s) = 0.90, p < 0.001), respectively. Findings suggest that expected match closeness (of an upcoming match) should not necessarily influence decision-making around practice design and match-play strategy. Additionally, the operational definitions developed for closely contested and one-sided matches developed here could be used in future studies to investigate different competitive contexts.

Objective The objectives of this study were to: (i) review and provide a narrative synthesis of threedimensional (3D) foot surface scanning methodological and statistical analysis protocols, and (ii) develop a set of recommendations for standardising the reporting of 3D foot scanning approaches.Methods A systematic search of the SCOPUS, ProQuest, and Web of Science databases were conducted to identify papers reporting 3D foot scanning protocols and analysis techniques.To be included, studies were required to be published in English, have more than ten participants, and involve the use of static 3D surface scans of the foot.Papers were excluded if they reported two-dimensional footprints only, 3D scans that did not include the medial arch, dynamic scans, or derived foot data from a full body scan. ResultsThe search yielded 78 relevant studies from 17 different countries.The available evidence showed a large variation in scanning protocols.The subcategories displaying the most variation included scanner specifications (model, type, accuracy, resolution, capture duration), scanning conditions (markers, weightbearing, number of scans), foot measurements and definitions used, and statistical analysis approaches.A 16-item checklist was developed to improve the consistency of reporting of future 3D scanning studies.Conclusion 3D foot scanning methodological and statistical analysis protocol consistency and reporting has been lacking in the literature to date.Improved reporting of the included subcategories could assist in data pooling and facilitate collaboration between researchers.As a result, larger sample sizes and diversification of population groups could be obtained to vastly improve the quantification of foot shape and inform the development of orthotic and footwear interventions and products.

Background: As obesity increases throughout the developed world, concern for the health of the population rises. Obesity increases the risk of metabolic syndrome, a cluster of conditions associated with type-2 diabetes. Correctly identifying individuals at risk from metabolic syndrome is vital to ensure interventions and treatments can be prescribed as soon as possible. Traditional anthropometrics have some success in this, particularly waist circumference. However, body size is limited when trying to account for a diverse range of ages, body types and ethnicities. We have assessed whether measures of torso shape (from 3D body scans) can improve the performance of models predicting the magnitude and distribution of body fat. Methods: From 93 male participants (age 43.1 ± 7.4) we captured anthropometrics and torso shape using a 3D scanner, body fat volume using an air displacement plethysmography device (BODPOD®) and body fat distribution using bioelectric impedance analysis. Results: Predictive models containing torso shape had an increased adjusted R2 and lower mean square error when predicting body fat magnitude and distribution. Conclusions: Torso shape improves the performance of anthropometric predictive models, an important component of identifying metabolic syndrome risk. Future work must focus on fast, low-cost methods of capturing the shape of the body.

Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (GM) is an established framework used for the statistical analysis of biological shape variation. These methods quantify biological shape variation after the effects of non-shape variation–location, rotation and scale–have been mathematically held constant, otherwise known as the Procrustes paradigm. The aim of this study was to determine whether shape measures, identified using geometric morphometrics, can provide additional information about the complexity of human morphology and underlying mass distribution compared to traditional body measures. Scale-invariant features of torso shape were extracted from 3D imaging data of 9,209 participants form the LIFE-Adult study. Partial least squares regression (PLSR) models were created to determine the extent to which variations in human torso shape are explained by existing techniques. The results of this investigation suggest that linear combinations of body measures can explain 49.92% and 47.46% of the total variation in male and female body shape features, respectively. However, there are also significant amounts of variation in human morphology which cannot be identified by current methods. These results indicate that Geometric morphometric methods can identify measures of human body shape which provide complementary information about the human body. The aim of future studies will be to investigate the utility of these measures in clinical epidemiology and the assessment of health risk.

The visco-elastic properties of a football influence how it bounces and therefore its performance in a game. Previously, high-speed camera footage has been used to quantify deformation, coefficient of restitution and contact time for an impact between a football and a rigid surface but these systems do not provide any information on the forces acting on the football during the impact. The aim of this study was to determine the repeatability of measuring the peak impact force, impulse, rise time and loading rate for four samples of the same model of football using a commercial force platform (Kistler 9281EA). A football impacted the floor-mounted piezoelectric-type force platform at 6.04 and 19.4 m s −1 . High absolute (coefficient of variation (CV) ≤ 10%) and relative (intraclass correlation coefficient (ICC) ≥ 0.94) repeatability was observed for repeated impacts at both velocities. The minimal detectable differences were calculated to evaluate the ability for the force platform to be used to make meaningful comparisons between footballs. For all metrics, the minimum detectable difference accounted for less than 5% of the mean value. Therefore, it can be concluded that provided the difference in impact metrics between football models exceeds the minimal detectable difference, the commercial force platform can be used to measure and detect differences in physical impact metrics between models of footballs.

Introduction: Compare the importance of complex (areas and volumes) and simple (lengths and girths) surface anthropometrics in the descriptive anthropometric assessment of the lower body of male cyclists from different disciplines. Method: Using a 3dMDBody5 3D surface imaging system and bespoke software (KinAnthroScan), anthropometrics of the lower body of 23 male non-cyclists and 57 elite male cyclists from different cycling disciplines: sprint (track and road (hill)), endurance (road, > 50 miles), time trial (road, < 50 miles) and mountain bike (cross-country and enduro) were collected. Results: Several anthropometrics differed between cycling groups and when compared to the non-cyclists group; the sprint group demonstrated the largest magnitude of difference with other cycling disciplines and the non-cyclists group, whereas the time trial and mountain bike groups demonstrated the least. Complex anthropometrics were able to distinguish between groups as effectively as simple anthropometrics, and in some cases, were able to distinguish differences that were unidentifiable through simple anthropometrics alone. Conclusions: Researchers, anthropometrists and practitioners should consider the collection and use of complex anthropometrics to improve the understanding of anthropometric differences within descriptive anthropometry, alongside adopting caution when researching groups of cyclists from different disciplines due to their differing anthropometric profiles - categorising them by discipline when possible.

The objective of this study was to determine the further care needs of people discharged from the hospital following a COVID-19 illness from April–September 2020. Methods: In partnership with an NHS trust in the UK, data analysis was undertaken by linking data from the Trust, to facilitated a triage process. The intention was to provide information in a format that enabled an examination of the population data and highlight any inequality in provision. Data were mapped onto the indices of multiple deprivation, and a range of text and graphical methods were used to represent the population data to the hospital leadership. The visual representation of the demographics and deprivation of people discharged during a critical period of the pandemic was intended to support planning for community services. The results demonstrated that just under half of those discharged were from the poorest fifth of the English population and that just under half were aged 75 or older. This reflected the disproportional effect of COVID-19 on those who were poorer, older or had pre-existing multiple morbidities. Referral to community or outpatient services was informed by the analysis, and further understanding of the diversity of the population health was established in the Trust. Conclusion: By identifying the population and mapping to the IMD, it was possible to show that over half of discharged patients were from deprived communities, and there was significant organisational learning bout using data to identify inequalities.. The challenge of planning services that target underserved communities remains an important issue following the pandemic, and lessons learnt from one health system are being shared.

Recent literature has suggested 3D surface imaging to be a potential method of estimating body composition. The aim of this study was to provide an overview of commercially available 3D surface imaging systems that provide body composition estimates. User and system details of complete commercially available whole body 3D surface imaging systems, which estimate body composition, were collated from May to June 2022. Six 3D body surface imaging systems were identified, each of which provided varying amounts of user and system details. As this information is necessary to ensure the correct selection of system, appropriate use, and interpretation of outputs, manufacturers should seek to publicly present more detailed user and system details, international standards groups and training associations should seek to encourage standardisation, and practitioners and researchers should request additional details where necessary and validate their system prior to use, and end users should cautiously interpret outputs without the availability of comprehensive user and system details.

Somatotype is an approach to quantify body physique (shape and body composition). Somatotyping by manual measurement (the anthropometric method) or visual rating (the photoscopic method) needs technical expertize to minimize intra- and inter-observer errors. This study aims to develop machine learning models which enable automatic estimation of Heath-Carter somatotypes using a single-camera 3D scanning system. Single-camera 3D scanning was used to obtain 3D imaging data and computer vision techniques to extract features of body shape. Machine learning models were developed to predict participants' somatotypes from the extracted shape features. These predicted somatotypes were compared against manual measurement procedures. Data were collected from 46 participants and used as the training/validation set for model developing, whilst data collected from 17 participants were used as the test set for model evaluation. Evaluation tests showed that the 3D scanning methods enable accurate (mean error < 0.5; intraclass correlation coefficients >0.8) and precise (test-retest root mean square error < 0.5; intraclass correlation coefficients >0.8) somatotype predictions. This study shows that the 3D scanning methods could be used as an alternative to traditional somatotyping approaches after the current models improve with the large datasets.

The accuracy and accessibility of methods to calculate body segment inertial parameters are a key concern for many researchers. It has recently been demonstrated that the magnitude and orientation of principal moments of inertia are crucial for accurate dynamic models. This is important to consider given that the orientation of principal axes is fixed for the majority of geometric and regression body models. This paper quantifies the effect of subject specific geometry on the magnitude and orientation of second moments of volume in the trunk segment. The torsos of 40 male participants were scanned using a 3D imaging system and the magnitude and orientation of principal moments of volume were calculated from the resulting geometry. Principal axes are not aligned with the segment co-ordinate system in the torso segment, with mean Euler angles of 11.7, 1.9 and 10.3 in the ZXY convention. Researchers using anatomical modelling techniques should try and account for subject specific geometry and the mis-alignment of principal axes. This will help to reduce errors in simulation by mitigating the effect of errors in magnitude of principal moments.

Lawn tennis rackets have changed considerably since the origins of the game. Early rackets were wooden, making them heavier and more flexible than modern designs made from fibre-polymer composites. The fundamental frequency of a freely suspended tennis racket is often used as an analogue to stiffness, despite it being dependent on mass. We estimate the bending stiffness of 525 rackets, dating from 1874 to 2017, using a uniform beam model that accounts for mass. The model suggests composite rackets are typically about twice as stiff as their wooden predecessors. Applying typical values of Young's modulus, density and second moment of area, the model was used to demonstrate the benefits of fibre-polymer composites for making lightweight, stiff rackets. Undergraduate students could make use of our large dataset of tennis rackets to explore these patterns themselves. They could also go on to measure the dimensions, mass and fundamental frequency of tennis rackets and model them as a uniform beam. Students could also apply the theory to other implements, like badminton and squash rackets or baseball and cricket bats.

Research has shown that short points (points of 0–4 shots) are crucial in determining the outcome of elite men’s and women’s grass court tennis matches. However, research has not explored the importance of short points in more detail to inform practice design. This study aimed to establish the prevalence and importance of individual rally lengths within short points (i.e. points of 0, 1, 2, 3 and 4 shots) in terms of winning elite grass court tennis matches. Using the recently-validated PWOL (Percentage of matches in which the Winner Outscored the Loser) method, point-level data from 211 men’s and 209 women’s Wimbledon singles matches between 2015 and 2017 were analysed, with short points stratified into individual rally lengths. Results revealed that 1 shot (aces and missed serve-returns) was the most common rally length, with 0 shots (double faults) the least common. Points won of 1 shot, 2 shots and 4 shots were associated with winning matches and can therefore be considered important, but points won of 0 shots and 3 shots were not associated with match outcome. These results highlight the importance of serving and returning strategies at Wimbledon, and indicate that serves and serve-returns should be afforded focus during grass court training. However, the findings appear to contravene anecdotal assertions that ‘serve plus one’ strategies (points won of 3 shots) are crucial in elite tennis, as they did not differentiate winning and losing players; so coaches should consider the associated practice designs and amount of time afforded to such strategies.

Markerless motion capture would permit the study of human biomechanics in environments where marker-based systems are impractical, e.g. outdoors or underwater. The visual hull tool may enable such data to be recorded, but it requires the accurate detection of the silhouette of the object in multiple camera views. This paper reviews the top-performing algorithms available to date for silhouette extraction, with the visual hull in mind as the downstream application; the rationale is that higher-quality silhouettes would lead to higher-quality visual hulls, and consequently better measurement of movement. This paper is the first attempt in the literature to compare silhouette extraction algorithms that belong to different fields of Computer Vision, namely background subtraction, semantic segmentation, and multi-view segmentation. It was found that several algorithms exist that would be substantial improvements over the silhouette extraction algorithms traditionally used in visual hull pipelines. In particular, FgSegNet v2 (a background subtraction algorithm), DeepLabv3+ JFT (a semantic segmentation algorithm), and Djelouah 2013 (a multi-view segmentation algorithm) are the most accurate and promising methods for the extraction of silhouettes from 2D images to date, and could seamlessly be integrated within a visual hull pipeline for studies of human movement or biomechanics.

Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMI), the waist-hip-ratio (WHR) and waist-by-height0.5 ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. The aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity.

We present a novel silhouette extraction algorithm designed for the binary segmentation of swimmers underwater. The intended use of this algorithm is within a 2D-to-3D pipeline for the markerless motion capture of swimmers, a task which has not been achieved satisfactorily, partly due to the absence of silhouette extraction methods that work well on images of swimmers. Our algorithm, FISHnet, was trained on the novel Scylla dataset, which contains 3,100 images (and corresponding hand-traced silhouettes) of swimmers underwater, and achieved a dice score of 0.9712 on its test data. Our algorithm uses a U-Net-like architecture and VGG16 as a backbone. It introduces two novel modules: a modified version of the Semantic Embedding Branch module from ExFuse, which increases the complexity of the features learned by the layers of the encoder; and the Spatial Resolution Enhancer module, which increases the spatial resolution of the features of the decoder before they are skip connected with the features of the encoder. The contribution of these two modules to the performance of our network was marginal, and we attribute this result to the lack of data on which our network was trained. Nevertheless, our model outperformed state-of-the-art silhouette extraction algorithms (namely DeepLabv3+) on Scylla, and it is the first algorithm developed specifically for the task of accurately segmenting the silhouettes of swimmers.