Assessment of a Microsoft Kinect-based 3D scanning system for taking body segment girth measurements: a comparison to ISAK and ISO standards.

Use of anthropometric data to infer sporting performance is increasing in popularity, particularly within elite sport programmes. Measurement typically follows standards set by the International Society for the Advancement of Kinanthropometry (ISAK). However, such techniques are time consuming, which reduces their practicality. Schranz et al. recently suggested 3D body scanners could replace current measurement techniques; however, current systems are costly. Recent interest in natural user interaction has led to a range of low-cost depth cameras capable of producing 3D body scans, from which anthropometrics can be calculated. A scanning system comprising 4 depth cameras was used to scan 4 cylinders, representative of the body segments. Girth measurements were calculated from the 3D scans and compared to gold standard measurements. Requirements of a Level 1 ISAK practitioner were met in all 4 cylinders, and ISO standards for scan-derived girth measurements were met in the 2 larger cylinders only. A fixed measurement bias was identified that could be corrected with a simple offset factor. Further work is required to determine comparable performance across a wider range of measurements performed upon living participants. Nevertheless, findings of the study suggest such a system offers many advantages over current techniques, having a range of potential applications.

Validity and repeatability of a depth camera-based surface imaging system for thigh volume measurement.

Complex anthropometrics such as area and volume, can identify changes in body size and shape that are not detectable with traditional anthropometrics of lengths, breadths, skinfolds and girths. However, taking these complex with manual techniques (tape measurement and water displacement) is often unsuitable. Three-dimensional (3D) surface imaging systems are quick and accurate alternatives to manual techniques but their use is restricted by cost, complexity and limited access. We have developed a novel low-cost, accessible and portable 3D surface imaging system based on consumer depth cameras. The aim of this study was to determine the validity and repeatability of the system in the measurement of thigh volume. The thigh volumes of 36 participants were measured with the depth camera system and a high precision commercially available 3D surface imaging system (3dMD). The depth camera system used within this study is highly repeatable (technical error of measurement (TEM) of <1.0% intra-calibration and ~2.0% inter-calibration) but systematically overestimates (~6%) thigh volume when compared to the 3dMD system. This suggests poor agreement yet a close relationship, which once corrected can yield a usable thigh volume measurement.

Effects of moment of inertia on restricted motion swing speed.

In many sports, the maximum swing speed of a racket, club, or bat is a key performance parameter. Previous research in multiple sports supports the hypothesis of an inverse association between the swing speed and moment of inertia of an implement. The aim of this study was to rigorously test and quantify this relationship using a restricted swinging motion. Eight visually identical rods with a common mass but variable moment of inertia were manufactured. Motion capture technology was used to record eight participants' maximal effort swings with the rods. Strict exclusion criteria were applied to data that did not adhere to the prescribed movement pattern. The study found that for all participants, swing speed decreased with respect to moment of inertia according to a power relationship. However, in contrast to previous studies, the rate of decrease varied from participant to participant. With further analysis it was found that participants performed more consistently at the higher end of the moment of inertia range tested. The results support the inverse association between swing speed and moment of inertia but only for higher moment of inertia implements.

Patient perceptions of three-dimensional (3D) surface imaging technology and traditional methods used to assess anthropometry.

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).

Methodological and statistical approaches for the assessment of foot shape using three-dimensional foot scanning: a scoping review.

OBJECTIVE: The objectives of this study were to: (i) review and provide a narrative synthesis of three-dimensional (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. RESULTS: The 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.

Torso Shape Improves the Prediction of Body Fat Magnitude and Distribution.

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.

Towards an Understanding of Population Health Data in a Single NHS Trust during COVID-19.

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.

Estimating somatotype from a single-camera 3D body scanning system.

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.

Modelling of human torso shape variation inferred by geometric morphometrics.

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.

Anatomical and principal axes are not aligned in the torso: Considerations for users of geometric modelling methods.

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.

How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study.

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.

Comparison of depth cameras for three-dimensional reconstruction in medicine.

KinectFusion is a typical three-dimensional reconstruction technique which enables generation of individual three-dimensional human models from consumer depth cameras for understanding body shapes. The aim of this study was to compare three-dimensional reconstruction results obtained using KinectFusion from data collected with two different types of depth camera (time-of-flight and stereoscopic cameras) and compare these results with those of a commercial three-dimensional scanning system to determine which type of depth camera gives improved reconstruction. Torso mannequins and machined aluminium cylinders were used as the test objects for this study. Two depth cameras, Microsoft Kinect V2 and Intel Realsense D435, were selected as the representatives of time-of-flight and stereoscopic cameras, respectively, to capture scan data for the reconstruction of three-dimensional point clouds by KinectFusion techniques. The results showed that both time-of-flight and stereoscopic cameras, using the developed rotating camera rig, provided repeatable body scanning data with minimal operator-induced error. However, the time-of-flight camera generated more accurate three-dimensional point clouds than the stereoscopic sensor. Thus, this suggests that applications requiring the generation of accurate three-dimensional human models by KinectFusion techniques should consider using a time-of-flight camera, such as the Microsoft Kinect V2, as the image capturing sensor.