scholarly journals Ensemble Learning for Skeleton-Based Body Mass Index Classification

2020 ◽  
Vol 10 (21) ◽  
pp. 7812
Author(s):  
Beom Kwon ◽  
Sanghoon Lee
Keyword(s):  
Body Mass Index ◽  
Ensemble Learning ◽  
Body Mass ◽  
Average Length ◽  
Average Height ◽  
Ensemble Model ◽  
Body Parts ◽  
K Nearest Neighbor ◽  
Proposed Model ◽  
Anthropometric Features

In this study, we performed skeleton-based body mass index (BMI) classification by developing a unique ensemble learning method for human healthcare. Traditionally, anthropometric features, including the average length of each body part and average height, have been utilized for this kind of classification. Average values are generally calculated for all frames because the length of body parts and the subject height vary over time, as a result of the inaccuracy in pose estimation. Thus, traditionally, anthropometric features are measured over a long period. In contrast, we controlled the window used to measure anthropometric features over short/mid/long-term periods. This approach enables our proposed ensemble model to obtain robust and accurate BMI classification results. To produce final results, the proposed ensemble model utilizes multiple k-nearest neighbor classifiers trained using anthropometric features measured over several different time periods. To verify the effectiveness of the proposed model, we evaluated it using a public dataset. The simulation results demonstrate that the proposed model achieves state-of-the-art performance when compared with benchmark methods.

scholarly journals Status of Certain Anthropometric Parameters of Males of Sasaram, India and Its Variation Due to Soybean Added Diet

2021 ◽  
Vol 11 (4) ◽  
pp. 313-319
Author(s):  
Dina Nath Pandit ◽  
Sunil Kumar ◽  
Anirudh Singh
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Experimental Studies ◽  
Average Height ◽  
Anthropometric Parameters ◽  
Anthropometric Features ◽  
The World ◽  
Core Elements ◽  
Soybean Diet ◽  
Present Standard

The anthropometric parameters are regarded as sensitive indicators. The core elements of anthropometric parameters are bodyweight, height and body mass index. To assess certain anthropometric features of males of Sasaram in respect to the standards and the variations in these features due to 60 days feeding of soybean added diet was the purpose of the work. Experimental studies indicate that soybean added diet might facilitate loss of bodyweight. All subjects were observed for anthropometric measurements after feeding of routine diet and soybean added diet. The average bodyweight was 63.65±8.97kg of volunteers aged 20-59 years with a height of 162.0+6.0cm in controlled condition among 2127 males. The average height of volunteers of 162.0+6.0cm was found less than the present standard of the Bihar, India as well as the world. On the other hand, the average of body mass index was 24.88±3.01 kg/m2 among the volunteers of the above age group and was found less than the present standard of the world but more than the standard of India. Consumption of soybean added diet was related to a moderately significant decreased weight (p<0.01) and body mass index. The study helps in establishing the anthropometric features of people of this area in comparison to the standard of the state and the country. Key words: Bodyweight, Body mass index, Males, Sasaram, Soybean diet.

Study regarding the bio-motor level and health of children from gymnasium level

2020 ◽  
pp. 1-9
Author(s):  
Dan Alexandru Szabo
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Anthropometric Measurements ◽  
Average Height ◽  
Mathematical Methods ◽  
Health Development ◽  
Health Level ◽  
Class Level ◽  
Flat Feet ◽  
Weight Problems

The investigation started from the need to find the level of bio-motor and health development in our Gymnasium School “Unirea” from Târgu Mureş. The research was also focused on discovering the children with BMI problems and finding the link between obesity and apparition of flat feet, spin and knee deficiencies. The methods of research were mainly experimental, we used anthropometric measurements of height, weight, body mass index and analyzed the parameters using statically and mathematical methods. The location of the study was the gymnasium level of the National College “Unirea” from Târgu Mureş, and involved 16 selected children with an average age 12.69 years old, 4 children with weight problems selected from every class level. The results of the investigation showed that the average height of the sample was 162.7 cm, weight 71 kg and a BMI average of 26.6. The BMI analyzed showed that obesity is an important factor in the apparition of other deficiencies, among students that were measured we also found 5 cases of kyphosis, 5 of scoliosis and 6 cases of flat feet. Conclusions of the investigation showed that BMI in youth is an important parameter in establishing the health level of children from gymnasium level and in preventing the apparition of the spine and feet deficiencies.

scholarly journals Computing the Average Body Mass Index: A Study with Systematic Sampling Using Auxiliary Information

2020 ◽  
Author(s):  
Gajendra K. Vishwakarma ◽  
Neha Singh ◽  
Surendra Pal Singh
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Numerical Study ◽  
Estimation Method ◽  
Auxiliary Information ◽  
The Body ◽  
Systematic Sampling ◽  
Body Parts ◽  
Observational Error ◽  
Systematic Sample

Abstract Background: The use of body mass index (BMI) could lead to over/under estimation of fat mass percentage. Systematic sampling is to be applied only if the given population is logically homogeneous, because systematic sample units are uniformly distributed over the population. The method of estimation for mean of the study variable under systematic sampling using auxiliary information has been proposed to estimate the body mass index (BMI).Methods: The measures of different body parts are taken as auxiliary variables. The observation available on different body parts are assumed to be recorded with observational error. Thus we also propose method of estimation for mean in the presence of observational error. Numerical study has been done to reveal the efficacy of the proposed procedure for estimation of mean. Simulation study has also been done to demonstrate the effect of observational error on the estimation of body mass index.Results: The properties of the proposed estimation method have been derived under large sampling approximation and obtained the conditions under which proposed method are more efficient. Conclusions: The study provides an easy approach and simplest way to obtain the BMI estimate with and without observational error. Thus the suggested method may be used by statistician for this problem and for many others similar problem in the estimation of mean.

Teaching Body Mass Index and Kleiber Law

2019 ◽  
Vol 01 (04) ◽  
pp. 1920010
Author(s):  
Dulli C. Agrawal
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Scaling Laws ◽  
Body Parts ◽  
Metabolic Rates ◽  
Human Beings ◽  
Spherical Head

Scaling laws advise that resting metabolic rates in animals and their corresponding body surfaces both should follow [Formula: see text] dependence. A pedagogic attempt has been made to validate this Kleiber law in case of human beings having spherical head and cylindrical arms, legs and trunk with the help of associated body mass index. It is observed that the metabolic rates of those persons who either lose or put on weight are not affected provided their body parts are functioning properly. It is suggested that matching body mass indices should also be worked out for animals.

scholarly journals A study of height, weight and body mass index in Nepalese

2021 ◽  
Vol 14 (2) ◽  
pp. 88-92
Author(s):  
Prakash Baral ◽  
Rami Shrestha ◽  
Ratindra Nath Shrestha ◽  
Dinesh Banstola ◽  
Rajesh Prajapati
Keyword(s):  
Body Mass Index ◽  
Health Status ◽  
Body Mass ◽  
Body Height ◽  
The Body ◽  
Anthropometric Measurement ◽  
Average Height ◽  
Important Indicator ◽  
Total Body Mass ◽  
Significant Difference

Introduction: The height measurement is an important anthropometric measurement which can be directly correlated with health status of an individual. Body weight of an individual refers to total body mass and is also important indicator of health status of people. Body mass index (BMI) is a key index for relating weight to height. It is defined as the body mass divided by the square of the body height, The BMI is an attempt to quantify the amount of body tissue mass  in an individual, and then categorize that the person as underweight, normal weight, overweight or obese. Objectives: To find out the average height and weight, to calculate BMI and find out its average value and to correlate height and weight in Nepalese population. Methodology: A cross sectional study was conducted in subjects from different parts of Nepal. Three hundred twenty one healthy subjects of 25-40 years of age group were studied. Height and weight of subjects were recorded and BMI was calculated. Data were analyzed using SPSS. Result: In overall Nepalese population, Mean height was found to be 156.6 ± 6.3 cm; mean weight 56.6 ± 11.4 kg and BMI 20.9 ± 1.8 kg/m2. Pearson’s correlation co-efficient(r) for height and weight was 0.88. Conclusion: There was partial positive correlation between height and weight. There was statistically significant difference in height, weight and BMI between Nepalese male and female(p<0.05).

scholarly journals Birthweight, Childhood Body Mass Index, Height and Growth, and Risk of Polycystic Ovary Syndrome

Obesity Facts ◽  
2021 ◽  
pp. 1-8
Author(s):  
Julie Aarestrup ◽  
Dorthe C. Pedersen ◽  
Peter E. Thomas ◽  
Dorte Glintborg ◽  
Jens-Christian Holm ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Polycystic Ovary Syndrome ◽  
Body Mass ◽  
Polycystic Ovary ◽  
Growth Patterns ◽  
Average Height ◽  
Tall Stature ◽  
Ovary Syndrome ◽  
Cox Regression Analysis ◽  
Childhood Body Mass Index

<b><i>Introduction:</i></b> Adult obesity is linked with polycystic ovary syndrome (PCOS), but the importance of body size at ages before PCOS is diagnosed is unknown. <b><i>Objective:</i></b> To investigate associations between a woman’s own birthweight, childhood body mass index (BMI), height and growth patterns in relation to her risk of PCOS. <b><i>Methods:</i></b> We included 65,665 girls from the Copenhagen School Health Records Register, born in the period 1960–1996, with information on birthweight and measured weight and height at the ages of 7–13 years. Overweight was defined using International Obesity Task Force (IOTF) criteria. From the Danish National Patient Register, 606 women aged 15–50 years were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox regression analysis. <b><i>Results:</i></b> Birthweight was not associated with PCOS. At the age of 7–13 years, girls with overweight had a higher risk of developing PCOS than girls without overweight; HR 2.83 (95% CI 2.34–3.42) at age 7 years and 2.99 (95% CI 2.38–3.76) at age 13 years. Furthermore, girls with overweight at both 7 and 13 years had a higher risk of developing PCOS than girls without overweight or overweight at only one age. Height was positively associated with PCOS risk at all ages. Girls who were persistently tall or changed from tall to average height had a higher risk of developing PCOS than girls with average height growth. <b><i>Conclusion:</i></b> Overweight and tall stature in childhood are positively associated with PCOS risk, but birthweight is not.

scholarly journals Analysis of anaerobic performance and the Body Mass Index measure of adolescents from different areas of Andalusian region (Spain)

2018 ◽  
Vol 11 (3) ◽  
Author(s):  
A De la Cruz-Campos ◽  
FL Pestaña-Melero ◽  
N Rico-Castro ◽  
JC De la Cruz-Campos ◽  
MB Cueto-Martín ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Rural Areas ◽  
Normal Weight ◽  
Overweight And Obesity ◽  
The Body ◽  
Average Height ◽  
Jump Test ◽  
Counter Movement Jump ◽  
Significant Difference

Objective: To analyze the behavior of the average height of jumps according to the Body Mass Index, and the sex of subjects, and to find significant differences between the variables measured in the anaerobic test of Counter Movement Jump test over 10 s and 60 s in adolescents according to place of residence. Method: We selected a huge sample of subjects to different places of residence and we categorized them in three levels; Urban – Interior, Urban – Coast and Rural – Interior. Their corporal composition were measured and analyzed, with this analysis we calculated the Body Mass Index, and categorized them by Body Mass Status (Underweight <18.5; Normal Weight 18.5–24.9; Overweight 25–29.9 and Obesity +30). Then, we measured the Jump 10 s. The next day, the Jump 60 s was measured, finding the anaerobic alactic and anaerobic lactic parameters. Results: The highest percentages of overweight and obesity (20.23%) were found in a Rural – Interior area, however, these have in turn the lowest percentages of underweight (10.66%). In the Counter Movement Jump test were not found significant difference in the measured obtained between subjects of Urban – Interior and Urban – Coast areas, but we found significant difference in the remaining comparisons. Conclusions: The significant difference in anaerobic values measured in adolescents, only reside purely in urban and rural areas, rejecting so a possible differentiation from the coast areas.

scholarly journals STUDY REGARDING THE VALUE OF THE PLAYERS ANTHROPOMETRIC INDICATORS MEMBERS OF THE ELITE EUROPEAN HANDBALL TEAMS QUALIFIED AT THE FINAL TOURNAMENTS

2021 ◽  
Vol 66 (2) ◽  
pp. 117-126
Author(s):  
IOSIF SANDOR ◽  
SIMINA-AURELIA NEAG
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Essential Role ◽  
Current Trend ◽  
The Body ◽  
Average Weight ◽  
Average Height ◽  
Anthropometric Parameters ◽  
Anthropometric Indicators ◽  
The World

Introduction. Handball players who manage to perform at the highest level have certain specific qualities. Through the results obtained in all world competitions, European national teams are considered the best teams in the world. Aim. The aim is to determine the current trend about the value of anthropometric indicators, primarily the body mass index, and its role in achieving performance. Materials and methods. The data of anthropometric parameters (age, height, weight, and body mass index - BMI) from 966 handball players who participated in 2016, 2018, and 2020 editions of the European Men''s Handball Championship had been analyzed. Next, the finalist and non-finalist teams'' BMI was analyzed, and then its evolution according to playing position. Results. The analysis shows that in the last three editions of the European Championship, an approximately constant value of the studied indicators is kept. The differences between the editions are not statistically significant. The average age is 27 years, the average weight is about 94 kg, the average height is 1.92 cm, and the BMI is 25. The body mass index did not register statistically significant differences for the same playing position in the last three editions analyzed. Conclusions. The data obtained from the study show what the current values of the leading anthropometric indicators of elite European handball players are. These indicators do not play an essential role in ranking in the first positions of the final tournament.

scholarly journals PSO Based Optimized Ensemble Learning and Feature Selection Approach for Efficient Energy Forecast

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2188
Author(s):  
Wafa Shafqat ◽  
Sehrish Malik ◽  
Kyu-Tae Lee ◽  
Do-Hyeun Kim
Keyword(s):  
Feature Selection ◽  
Ensemble Learning ◽  
Optimization Technique ◽  
Ensemble Model ◽  
Success Rates ◽  
Proposed Model ◽  
Random Samples ◽  
Feature Selection Approach ◽  
Energy Forecast ◽  
Fine Tune

Swarm intelligence techniques with incredible success rates are broadly used for various irregular and interdisciplinary topics. However, their impact on ensemble models is considerably unexplored. This study proposes an optimized-ensemble model integrated for smart home energy consumption management based on ensemble learning and particle swarm optimization (PSO). The proposed model exploits PSO in two distinct ways; first, PSO-based feature selection is performed to select the essential features from the raw dataset. Secondly, with larger datasets and comprehensive range problems, it can become a cumbersome task to tune hyper-parameters in a trial-and-error manner manually. Therefore, PSO was used as an optimization technique to fine-tune hyper-parameters of the selected ensemble model. A hybrid ensemble model is built by using combinations of five different baseline models. Hyper-parameters of each combination model were optimized using PSO followed by training on different random samples. We compared our proposed model with our previously proposed ANN-PSO model and a few other state-of-the-art models. The results show that optimized-ensemble learning models outperform individual models and the ANN-PSO model by minimizing RMSE to 6.05 from 9.63 and increasing the prediction accuracy by 95.6%. Moreover, our results show that random sampling can help improve prediction results compared to the ANN-PSO model from 92.3% to around 96%.

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