Human Body Measurement Research Articles

Effects of the Anthropometrical Variables on Swimming Performance

Anthropometrical word generated from ancient Greek word. Anthropos represent human and matron represent measurement. Anthropology mainly purposes for the identification of human body measurement. Anthropology is systematic process which involves the primary dimensional properties of human body like body weight, Arm length, Foot length etc. Its include shape and size of the human body. In today era Anthropometrical play’s major role in measurement of human body such as shape and size. Anthropometry helps in different field like clothing design industrial design. Anthropometry history contains different types of thought like such as scientific biological criminology, paleoanthropology, biological anthropology and it create correlation between mental typology personality and other factors. In different time period of history, applications of anthropometry have ranged scientific description and epidemiological analysis to rationales for eugenics for social movements Swimming is team game and also an individual game which use the one entire body to move in the water. swimming is kind of expensive game it required large amount of infrastructure. Its only perform in open water like sea or lake and standard swimming pool. In swimming is more popular in Olympics .in swimming different type of stroke are there like freestyle stroke, breast stroke, butterfly stroke, back stroke etc. swimmers players have to perform different kind of stroke in different event and also only in individual events, four swimmers can take part in either a freestyle or medley relay.

AdaBoost algorithm for the recognition of young women’s body shapes based on 2D images

Classifying and recognizing the human body shape during human body measurements based on 2D images helps to improve measurement accuracy. In this paper, 430 young women's 2D body images were selected to establish 2D body datasets. The characteristic indices used to represent the body shape in 2D images were extracted by computer vision technology, namely the body height pixel value, projected unit area, and projected area ratio of the front and side of the body. The two-step cluster model was used to classify the body shape into three clusters: the tall, flat, and medium fatness type; the short, thin, and medium roundness type; and the round, fat, and medium height type. Then, the decision tree model and AdaBoost algorithm, an ensemble learning algorithm with the decision tree as the weak classifier, were used to recognize the body shape. The results show that the recognition accuracy of the decision tree recognition model was 93.19%. The body shape recognition method using AdaBoost achieved a better recognition effect than the decision tree model, and the recognition accuracy of the test set reached 97.35%. Through comparative study, we found that the recognition accuracy of the 2D body shape recognition method based on AdaBoost was improved and that the recognition accuracy was relatively stable. This study provides a new method for the recognition of human body shape in clothing customization and online shopping.

Evacuation scenario optimization in buildings with human anthropometric characteristics

Emergency evacuations are critical situations that threaten people's lives and safety, necessitating robust planning and prevention strategies. Anthropometric data, which are numerical expressions of human body measurements, play a vital role in architectural design by helping determine safe evacuation routes. This data is crucial for understanding the physical characteristics and mobility of building occupants, allowing for optimized evacuation routes that accommodate the needs of various groups, such as the elderly, children, and individuals with physical disabilities. The Social Forces Model (SFM) is an important tool used to understand the behavior and movement of crowds, modeling these aspects mathematically by considering social interactions and environmental factors. This study develops a system to enhance emergency evacuation scenarios in buildings using anthropometric data and SFM. This system analyzes the evacuation process and identifies optimal routes, contributing significantly to ensuring safety and minimizing damage during disasters. The research shows that using anthropometric data and SFM in architectural design is essential for effective emergency evacuation planning and management. Simulations that incorporate the diverse physical characteristics of people demonstrate notable improvements in evacuation times compared to those using fixed values, with up to 10.20 % improvement in single-exit scenarios and up to 13.45 % in two-exit scenarios. Furthermore, evacuation routes are optimized using SFM, and histograms are employed to identify the most preferred routes during panic situations. This data-driven approach informs the design of building and floor layouts, as well as the materials and decorations used, ensuring that evacuation routes remain clear and accessible. Removing obstacles and facilitating easy passage during emergencies significantly enhances the effectiveness of evacuations. Overall, the integration of anthropometric data and SFM in building design is shown to create faster and safer evacuation processes, ultimately improving emergency response and safety.

Simple Hybrid Camera-Based System Using Two Views for Three-Dimensional Body Measurements

Using a single RGB camera to obtain accurate body dimensions, rather than measuring these manually or via more complex multicamera systems or more expensive 3D scanners, has a high application potential for the apparel industry. We present a system that estimates upper human body measurements using a hybrid set of techniques from both classic computer vision and recent machine learning. The main steps involve (1) using a camera to obtain two views (frontal and side); (2) isolating in the image pair a set of main body parts; (3) improving the image quality; (4) extracting body contours and features from the images of body parts; (5) indicating markers on these images; (6) performing a calibration step; and (7) producing refined final 3D measurements. We favour a unique geometric shape, that of an ellipse, to approximate human body main horizontal cross-sections. We focus on the more challenging parts of the body, i.e., the upper body from the head to the hips, which, we show, can be well represented by varying an ellipse’s eccentricity for each individual. Then, evaluating each fitted ellipse’s perimeter allows us to obtain better results than the current state-of-the-art methods for use in the fashion and online retail industry. In our study, we selected a set of two equations, out of many other possible choices, to best estimate upper human body section circumferences. We experimented with the system on a diverse sample of 78 female 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 ±1 cm average differences, which are sufficient for many applications, including online retail.

Enhancing human parsing with region‐level learning

AbstractHuman parsing is very important in a diverse range of industrial applications. Despite the considerable progress that has been achieved, the performance of existing methods is still less than satisfactory, since these methods learn the shared features of various parsing labels at the image level. This limits the representativeness of the learnt features, especially when the distribution of parsing labels is imbalanced or the scale of different labels is substantially different. To address this limitation, a Region‐level Parsing Refiner (RPR) is proposed to enhance parsing performance by the introduction of region‐level parsing learning. Region‐level parsing focuses specifically on small regions of the body, for example, the head. The proposed RPR is an adaptive module that can be integrated with different existing human parsing models to improve their performance. Extensive experiments are conducted on two benchmark datasets, and the results demonstrated the effectiveness of our RPR model in terms of improving the overall parsing performance as well as parsing rare labels. This method was successfully applied to a commercial application for the extraction of human body measurements and has been used in various online shopping platforms for clothing size recommendations. The code and dataset are released at this link https://github.com/applezhouyp/PRP.

Non-contact Measurement Using Ultrasonic Technology for Human Anthropometric: A Narrative Review

Introduction: Stunting is a public health priority in low- and middle-income countries. Thus, the validity and reliability of anthropometric measurement tools become critical for early stunting detection in children. 
 Objective: This article aims to review the use of ultrasonic sensors in human anthropometric and body measurements.
 Methods: We conducted a narrative review of articles regarding the ultrasonic sensor for measuring anthropometrics in the human body between 2016 and 2022. We focused particularly on the use of ultrasonic sensors in children’s anthropometrics, body size, and body measurements.
 Results: According to the findings, the majority of non-contact measurements using ultrasonic sensors were applied to adults, though several studies also involved pregnant women to measure foetus size. These studies showed that ultrasonic sensors were beneficial as they served as accurate, reproducible, affordable, and easy-to-use tools.
 Conclusion: Future studies are warranted to understand the significance of the non-contact measurements for children’s anthropometrics, especially for early stunting detection.

Ergonomics considerations for raising the efficiency of indoor lighting fixture

Lighting plays an important role in human life in general and in the internal spaces in particular, whether from a functional and aesthetic point of view, light leads human movement within the space, and without light it is not possible to determine the aesthetic and sensory character of the internal space of the user's environment, as the use of light in the right place and for lighting within the surrounding human environment and not applying the rules Ergonomics leads to annoying or weak incandescent lighting that is insufficient for the desired function or is highlighted on a part that has no importance, and here comes the role of ergonomics in linking the desired function of each lighting unit and the surrounding space and achieving the highest functional efficiency of each lighting unit . Problem of research : Improving the working environment is one of the most important factors to increase human productivity, Since proper lighting is one of the most important factors of the work environment, Its effects on people and workplaces are far-reaching and dim lighting can have a negative impact on productivity, job performance, job satisfaction and human physical health , Given that people receive 90% of their information visually, and the failure to apply ergonomics rules in lighting units in the work environment, whether housing, office, or others, leads to eye fatigue, irritation, and blurred vision, whether due to poor lighting, intense glare, or ill-considered lighting. It can also cause bending forward or backward in order to see better, which creates awkward physical postures that can contribute to diseases of the musculoskeletal system and other physical diseases A large part of the poor lighting is due to non-application of ergonomics rules based on careful study of the product and the surrounding environment. With the user and the measurements of the human body and the function that each unit performs in its correct place and with the required intensity. research aims :- • Improving the efficiency of indoor lighting units • Determining some ergonomics rules that must be available in the interior lighting units. research importance :- • The effective role of the designer lies in achieving compatibility between the user and the work environment surrounding him, especially the surrounding lighting units, which help him to accomplish his daily tasks in a better and faster way. Human body measurements to achieve the highest productivity and reduce or prevent negative effects on the body and achieve the desired function of lighting with the highest efficiency. research results : 1- The science of ergonomics is concerned with achieving compatibility between the user and the surrounding environment, and this is achieved by studying the problems faced by the user, an accurate study based on the measurements of the human body and a study of the proportions and surrounding spaces in the work environment. 2- Achieving ergonomics rules on lighting units surrounding the human being allows interaction and harmony with the work environment, which leads to increased productivity to employ lighting elements in their proper places and control the intensity of lighting appropriate for each desired job. 3- The research presented some ergonomic considerations on which the interior lighting units must be based to match the measurements and needs of the human body to perform the desired function better and with higher efficiency. 4- The considerations for each lighting unit differ according to the function required of it. The directed office lighting is different from the diffuse lighting, and it differs from the ground or decorative lighting. 5- Comfort is one of the most important elements that we reach when applying the rules of ergonomics, and not only comfort, but up to the point of enjoying the work environment. 6- The optimal use of lighting units with their appropriate intensity and the invention of new ways to automatically close the lighting units, which leads to rationalization of energy consumption, a more sustainable orientation, and a reduction in wasted energy.

Multi-frame optimisation for active stereo with inverse renderingto obtain consistent shape and projector-camera posesfor 3D endoscopic system

ABSTRACT 3D measurement of inside human body becomes important and several techniques have been proposed. Among them, ultra-small pattern projector with off-the-shelf endoscope is promising because of stability, accuracy and cost-effectiveness. One drawback of the system is that since 3D shape is reconstructed for each frame while endoscope head is moving, they are not registered. In addition, shapes are distorted independently, since the position of the projector cannot be fixed to the head. In this paper, we propose a novel bundle adjust (BA) algorithm to solve both distortion and shape registration problems for a 3D endoscope system based on pattern projection. By using the proposed method, multiple measurements that potentially have scale inconsistencies and shape distortions are registered, with simultaneous correction of inter-frame inconsistencies. The effectiveness of the technique is proved for measurements of concave shapes made of clay, phantom models, and a real stomach of a pig.

Position Estimation for the Capsule Endoscope Using High-Definition Numerical Human Body Model and Measurement

Position Estimation for the Capsule Endoscope Using High-Definition Numerical Human Body Model and Measurement

Linear Regression vs. Deep Learning: A Simple Yet Effective Baseline for Human Body Measurement.

We propose a linear regression model for the estimation of human body measurements. The input to the model only consists of the information that a person can self-estimate, such as height and weight. We evaluate our model against the state-of-the-art approaches for body measurement from point clouds and images, demonstrate the comparable performance with the best methods, and even outperform several deep learning models on public datasets. The simplicity of the proposed regression model makes it perfectly suitable as a baseline in addition to the convenience for applications such as the virtual try-on. To improve the repeatability of the results of our baseline and the competing methods, we provide guidelines toward standardized body measurement estimation.

Design and fabrication of optical filters for infrared imaging temperature measurement

The four kinds of infrared filters for infrared imaging temperature measurement of human body are designed with Ge/ZnS and ZnS/YbF3 film stacks on germanium and zinc selenide substrates, respectively. The characteristics of Ge/ZnS and ZnS/YbF3 film stack on germanium and zinc selenide substrates are discussed based on the analysis and comparison of optical and non-optical properties. The infrared filters designed by Ge/ZnS have fewer film layers, smaller film thickness and lower transmittance in cut-off region than those designed by ZnS/YbF3 film stack. The infrared filters composing of Ge/ZnS film stack on the germanium substrate have been produced. The average transmittance measured in the mid and long-wave infrared (5.5–12 µm) band is about 90%, and the transmittance of the cut-off band is less than 1%. The coating samples can endure the adhesion and environmental tests.

Automatic 3D human body landmarks extraction and measurement based on mean curvature skeleton for tailoring

Automatic 3D human body measurement is a crucial issue for tailoring and made-to-measure. This paper presents a novel framework for 3D human landmarks extraction and measurement. The proposed approach first segments the 3D human body into 13 parts by utilizing an improved Mean Curvature Skeleton (MCS) algorithm, in which we modify the Laplacian operator used in the original MCS with mesh saliency to enable the segmentation boundaries to be closer to the human joints. Based on the human segmentation, K-Nearest Neighbors, linear modeling, and geometric methods are employed to extract at least 21 landmarks. Many essential landmarks, such as acromion, elbow, crotch, etc., are extracted in new ways. To our best knowledge, this is the first paper to propose a generalized solution to approximate the elbow point for arbitrary arm poses in the automatic 3D human measurement systems. Subsequently, various anthropometric measurements can be calculated according to the landmarks extracted automatically. The proposed method is validated on the public datasets and our real scans, and the experimental results have verified that the proposed approach is efficient and effective in processing various 3D human bodies.

The Importance of Anthropometric Research to the Malaysian Population: A Systematic Review

The importance of anthropometric research cannot be denied. Anthropometric research is defined as research related to human body measurements. This research is extensively conducted in many fields, such as product design, apparel manufacturing, health and medical care, and forensic research. This paper aims to review the existing articles on the importance of anthropometric research to the Malaysian population and determine how the related research can be further explored. This paper used PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) to retrieve the articles through its identification, screening and eligibility processes. The search for articles related to PRISMA resulted in 15 articles identified through Scopus and Web of Science databases. Articles were grouped based on themes using thematic analysis. The themes were created based on seven perceived benefits of anthropometric research: easy to use, fit, well-being, welfare, safety, work efficiency, and identity verification. Finally, at the end of this paper, several conclusions concerning the importance of anthropometric research for the reference of future scholars were presented.

Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification

Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.

Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement.

In this paper, the key technology of interferometric microwave thermometer is studied, the research can be applied to the temperature measurement of human body and subcutaneous tissue. This paper proposes a hardware architecture of interferometric microwave thermometer with 2 GHz bandwidth, in which the phase shifter is used to correct phase error and the quadrature demodulator is used to realize autocorrelation detection function. The results show that when input power is 7 dBm, the detection sensitivity can reach 176.54 mV/dBm and the temperature resolution of the microwave radiometer can reach 0.4 K. Correction algorithm is designed to improve the accuracy of temperature measurement. After correction, the phase error is reduced from 40° to 1.4° and when temperature changes 0.1 °C, the voltage value changes obviously. Step-by-step calibration and overall calibration are used to calibrate the device. Inversion algorithm can determine the relationship between physical temperature and output voltage. The mean square error of water temperature inversion by multiple linear regression algorithm is 0.607 and that of BP neural network algorithm is 0.334. The inversion accuracy can be improved by reducing the temperature range. Our work provides a promising realization of accurate, rapid and non-contact detection device of human body temperature.

Selecting Promising Junior Swimmers in Egypt Using Automated Biometric Algorithms of Image Processing and Fuzzy Concepts

Modern sports need a great physical and psychological effort from young athletes to reach high performance levels. Stature length, leg length, foot length, arm length, hand length, shoulder width, hip width, chest width and weight are the anthropometric characteristics that affect swimmers' performances. This paper introduces new techniques to select promising junior swimmers in Egypt. It develops two automated algorithms to select junior swimmer depending on their anthropometric measurement. The first technique uses Canny filter to develop the first algorithm, while the second one uses the Fuzzy concepts. The proposed algorithms make use of the image processing technique to handle the anthropometric measurements, by detecting the human body feature points automatically from the front and side images. The 101 feature points extract automatically from 36 human body measurements, while swimming games needs only 8 body dimensions from these 36 human body measurements. Therefore, the proposed system is not limited to swimming sports but can also be applied to other sports. Moreover, the experimental results and the corresponding statistical analysis show the high accuracy and advantages of the proposed algorithms. The first algorithm improved the results that could have obtained using the well-known fully vision-based automatic human body method by 22.23%, 15.9%,29.41%, and 27.5%, for stature length, arm length, leg length, and shoulder width, respectively. Also, it gave the best results for Leg Length, and Shoulder width, while the second one yielded the best result for Stature Length.

Selected dynamic anthropometrics and body characteristics for posture corrector fit

Correct body posture is a balanced musculoskeletal body position; however, today many people face severe posture defects, and their body posture may be far from a normal, causing progressive musculoskeletal deformities and pain, as well as affecting the functionality and appearance of the body. Human daily habits, lack of physical activities and overall a sedentary lifestyle cause such phenomena. The research focuses on studies of human body measurements and body characteristics while wearing posture-corrective equipment for the assessment of the effectiveness of different posture correctors (abbreviated as PoC). Four test-persons were selected and scanned using 3D anthropometrical scanner in relaxed stand position wearing five different posture correctors for a prolonged period of time in order to determine the effectiveness and functionality of each PoC. Four distance (linear) human body measurements were gained to quantify postural changes - scapula position depth, upper torso position, shoulder projection height and hip-waist depth. General feedbacks on each subject impression of wearing PoCs were also received. Correction of posture could serve as a preventive or treatment for spine-related problems; though, commercially available correctors could negatively affect wearer’s health due to non-conformity of the design and/or used material. Therefore, PoC selection and wearing procedures should be solved with more personalized and customized approaches.

Design of Classroom Furniture for Use at Tertiary Institutions

The design of classroom desktop-chairs (one size fits all) in many institutions is usually done with no consideration of ergonomics. Therefore, there is a mismatch between classroom desktop-chairs dimensions and students' anthropometric characteristics. This may cause musculoskeletal disorders and affect learning effectiveness due to sitting for a long time in an awkward position. Ergonomically designed furniture is known to reduce musculoskeletal disorders and improve the attentiveness of students in the classroom environment. This research, therefore, aimed to use the concept of ergonomics to design classroom desktop-chair for students in Uasin-Gishu County. Anthropometric data was collected from a total of three hundred and eighty-two (382) students of both genders. The selected tertiary institutions for the survey were Moi University (MU), University of Eldoret (UoE), Rift Valley Technical Training Institute (RVTTI) and The Eldoret National Polytechnic (TENP). Fourteen (14) anthropometric measurements were taken from students with the help of anthropometric tools. The research applied fundamental engineering principles of product design and was carried out in compliance with ISO 7250-1: (Basic human body measurements for technological design part 1: Body measurement definitions and landmarks). The data obtained was analysed using Minitab 17.0 statistical package, to get the mean, standard deviation, minimum, maximum, 5 th , 50 th and 95 th percentiles. SolidWorks 2019, was used to design a desktop-chair. The analysed anthropometric data set was used to design, a suitable classroom desktop-chair. One type of ergonomically suitable classroom desktop-chair design was proposed to improve the match between classroom desktop-chairs dimensions and students' anthropometric characteristics. The analysed anthropometric data set can be used for the design of classroom desktop-chairs for students not only in the selected tertiary institutions but all over Kenya. Keywords: Musculoskeletal disorders, Awkward posture, Classroom environment. DOI: 10.7176/ISDE/11-5-05 Publication date: September 30 th 2020

Mechanically driven strategies to improve electromechanical behaviour of printed stretchable electronic systems

Stretchable electronics promise to extend the application range of conventional electronics by enabling them to keep their electrical functionalities under system deformation. Within this framework, development of printable silver-polymer composite inks is making possible to realize several of the expected applications for stretchable electronics, which range from seamless sensors for human body measurement (e.g. health patches) to conformable injection moulded structural electronics. However, small rigid electric components are often incorporated in these devices to ensure functionality. Under mechanical loading, these rigid elements cause strain concentrations and a general deterioration of the system’s electrical performance. This work focuses on different strategies to improve electromechanical performance by investigating the deformation behaviour of soft electronic systems comprising rigid devices through Finite Element analyses. Based on the deformation behaviour of a simple stretchable device under tensile loading, three general strategies were proposed: local component encapsulation, direct component shielding, and strain dispersion. The FE behaviour achieved using these strategies was then compared with the experimental results obtained for each design, highlighting the reasons for their different resistance build-up. Furthermore, crack formation in the conductive tracks was analysed under loading to highlight its link with the evolution of the system electrical performance.

Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems

Millimeter wave (mmWave) bands have been utilized for the fifth generation (5G) communication systems and will no doubt continue to be deployed for beyond 5G (B5G). However, the underlying channels are not fully investigated at multi-frequency bands and in multi-scenarios by using the same channel sounder, especially for the outdoor, multiple-input multiple-output (MIMO), and vehicle-to-vehicle (V2V) conditions. In this paper, we conduct multi-frequency multi-scenario mmWave MIMO channel measurements with 4 × 4 antennas at 28, 32, and 39 GHz bands for three cases, i.e., the human body and vehicle blockage measurements, outdoor path loss measurements, and V2V measurements. The channel characteristics, including blockage effect, path loss and coverage range, and non-stationarity and spatial consistency, are thoroughly studied. The blockage model, path loss model, and time-varying channel model are proposed for mmWave MIMO channels. The channel measurement and modeling results will be of great importance for further mmWave communication system deployments in indoor hotspot, outdoor, and vehicular network scenarios for B5G.