Describing the children's body shape by means of Geometric Morphometric techniques

Medialdea, Laura; Bazaco, Cayetana; Campo, Manuel Domingo D'Angelo del; Sierra-Martínez, Carlos; González‐José, Rolando; Vargas, Antonio; Marrodán, María Dolores

doi:10.1002/ajpa.23779

Cited by 8 publications

(5 citation statements)

References 66 publications

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“…Successful scans were processed for only 4 in 10 children included in the study as a result of higher refusal rates, poorer scan quality, and a large number of scans unsuccessfully transmitted. Although high refusal rates have been reported in previous studies of 3D scan technologies, the magnitude of the problem in South Sudan is distinct [ 5 , 8 ]. COVID-19 pandemic–related social distancing orders limited the number of children, particularly younger children, measured in a supine position available to use for validating the device algorithm before the initiation of field pilots and data collection.…”

Section: Discussionmentioning

confidence: 99%

“…A sample of 485 children was targeted to achieve desired precision for estimating prevalence of global acute malnutrition, the primary survey aim. This sample was determined to be sufficient to detect a difference of 0.17 cm for height/length and 0.09 cm for MUAC given an α of .05, power of 0.8, and SDs observed in previous studies [ 5 ]. All children aged 6 to 59 months within selected households whose primary caregiver gave verbal informed consent were eligible to participate.…”

Section: Methodsmentioning

confidence: 99%

“…Preliminary validation studies for software aiming to directly classify acute malnutrition have encountered methodological as well as logistic challenges. The Photo Diagnosis App validation phase study in Spain and Senegal found high accuracy of diagnosis but suggested significant morphometric differences among the populations sampled, implying a need to investigate this morphological variability [ 5 , 6 ]. The researchers involved in the study noted that, although morphological variability could likely be overcome with machine learning, the approach proved very expensive compared with current technologies and that capturing a viable scan required conditions that could not be repeated in the field (AV Brizuela, personal communication, February 25, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

Leidman¹,

Jatoi²,

Bollemeijer³

et al. 2022

JMIR Biomed Eng

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Background Adoption of 3D imaging systems in humanitarian settings requires accuracy comparable with manual measurement notwithstanding additional constraints associated with austere settings. Objective This study aimed to evaluate the accuracy of child stature and mid–upper arm circumference (MUAC) measurements produced by the AutoAnthro 3D imaging system (third generation) developed by Body Surface Translations Inc. Methods A study of device accuracy was embedded within a 2-stage cluster survey at the Malakal Protection of Civilians site in South Sudan conducted between September 2021 and October 2021. All children aged 6 to 59 months within selected households were eligible. For each child, manual measurements were obtained by 2 anthropometrists following the protocol used in the 2006 World Health Organization Child Growth Standards study. Scans were then captured by a different enumerator using a Samsung Galaxy 8 phone loaded with a custom software, AutoAnthro, and an Intel RealSense 3D scanner. The scans were processed using a fully automated algorithm. A multivariate logistic regression model was fit to evaluate the adjusted odds of achieving a successful scan. The accuracy of the measurements was visually assessed using Bland-Altman plots and quantified using average bias, limits of agreement (LoAs), and the 95% precision interval for individual differences. Key informant interviews were conducted remotely with survey enumerators and Body Surface Translations Inc developers to understand challenges in beta testing, training, data acquisition and transmission. Results Manual measurements were obtained for 539 eligible children, and scan-derived measurements were successfully processed for 234 (43.4%) of them. Caregivers of at least 10.4% (56/539) of the children refused consent for scan capture; additional scans were unsuccessfully transmitted to the server. Neither the demographic characteristics of the children (age and sex), stature, nor MUAC were associated with availability of scan-derived measurements; team was significantly associated (P<.001). The average bias of scan-derived measurements in cm was −0.5 (95% CI −2.0 to 1.0) for stature and 0.7 (95% CI 0.4-1.0) for MUAC. For stature, the 95% LoA was −23.9 cm to 22.9 cm. For MUAC, the 95% LoA was −4.0 cm to 5.4 cm. All accuracy metrics varied considerably by team. The COVID-19 pandemic–related physical distancing and travel policies limited testing to validate the device algorithm and prevented developers from conducting in-person training and field oversight, negatively affecting the quality of scan capture, processing, and transmission. Conclusions Scan-derived measurements were not sufficiently accurate for the widespread adoption of the current technology. Although the software shows promise, further investments in the software algorithms are needed to address issues with scan transmission and extreme field contexts as well as to enable improved field supervision. Differences in accuracy by team provide evidence that investment in training may also improve performance.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

Leidman¹,

Jatoi²,

Bollemeijer³

et al. 2022

JMIR Biomed Eng

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“…PCA has been used to study shape variation or extract relevant information for the development of fit test panels, defining sizing systems, or determining product dimensions [29,33,34]. In addition, PCA has been conducted in order to study body shape differences in children [35]. The input variables for a PCA can vary from measurements, landmark locations or point-cloud data/3D geometric models [1,5,11,[36][37][38].…”

Section: Introductionmentioning

confidence: 99%

The Variation in 3D Face Shapes of Dutch Children for Mask Design

et al. 2021

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The use of 3D anthropometric data of children’s heads and faces has great potential in the development of protective gear and medical products that need to provide a close fit in order to function well. Given the lack of detailed data of this kind, the aim of this study is to map the size and shape variation of Dutch children’s heads and faces and investigate possible implications for the design of a ventilation mask. In this study, a dataset of heads and faces of 303 Dutch children aged six months to seven years consisting of traditional measurements and 3D scans were analysed. A principal component analysis (PCA) of facial measurements was performed to map the variation of the children’s face shapes. The first principal component describes the overall size, whilst the second principal component captures the more width related variation of the face. After establishing a homology between the 3D scanned face shapes, a second principal component analysis was done on the point coordinates, revealing the most prominent variations in 3D shape within the sample.

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“…The optimal time for skull repair in young Chinese children with skull defects was studied by Hou et al (2014), who found that children aged 3 years or older may receive skull repair. Medialdea et al (2019) visualized and quantified body shape differences in healthy children aged 6 to 59 months with optimal nutrition using geometric morphometric techniques.…”

Section: Introductionmentioning

confidence: 99%

Morphometric Variations and Growth Analysis of the Side Face Profiles of Chinese Children

Chen

Liu

et al. 2021

The Cleft Palate Craniofacial Journal

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Objective: We aim to use geometric morphometric methods to analyze the contours of the side face profile and its variations in 116 children in Hunan province, China, in order to reveal common morphological features and growth of the side face profiles of Chinese children. Design: We photographed the side faces with consistent standardized procedures. Thirty-seven landmarks were recorded, which comprehensively reflected the facial sagittal plane. The collection of coordinate data regarding landmarks was conducted by tpsDig software. Other analyses, such as average shape analysis, principal component analysis, variations analysis, and allometric analysis, were conducted using tpsRelw and tpsRegr. Result: Based on the 37 landmarks, principal component analysis was used on the profiles of boys and girls. The result shows that PC1 and PC2 account for 35.46% and 27.44% of the side face contour variations, respectively. There is no significant difference in the side profiles of boys and girls. Overlapping distributions between the boys and girls occurred. A significant difference occurs when principal component analysis was used on the side profiles of children and adults. Conclusions: There is a significant difference in the side face profiles between adult males and females. Adult males have a higher brow (the 8th landmark) than females, and adult females have a more curved forehead. However, the side face profiles of boys and girls around 10 years of age are generally similar, which suggests that the significant difference in side face profiles between adult males and females may be formed after the age of 10. This study is of great significance for both orthodontists and pediatricians to use different norms for kids and adults and different norms for males and females for each of those age groups.

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Describing the children's body shape by means of Geometric Morphometric techniques

Abstract: 665Stable isotope variation in savanna chimpanzees (Pan troglodytes verus) indicate avoidance of energetic challenges through dietary compensation at the limits of the range

Cited by 8 publications

References 66 publications

Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan

The Variation in 3D Face Shapes of Dutch Children for Mask Design

Morphometric Variations and Growth Analysis of the Side Face Profiles of Chinese Children

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