Correlation of body composition parameters and anthropometric somatotypes with <i>Prakriti</i> body types among the Meitei adults of Manipur, India

Konjengbam, Henry; Devi, Yumnam Leona; Meitei, Sanjenbam Yaiphaba

doi:10.1080/03014460.2021.1919205

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…In general, there was no significant percentage increase or decrease in the body parameters measured except for mesomorphy in volleyball, which showed an increase of 14.458%. However, changes in body parameters, however small, are manifested in changes in overall somatotype (Figure 2); this relationship was already corroborated in various sporting and athletic disciplines [64].…”

Section: Discussionsupporting

confidence: 53%

Comparison of Sports Performance and Kinanthropometric Profiles of Elite Female Basketball and Volleyball Players over the Course of a Competitive Season

2023

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In order to maximize sports performance of team sportswomen, knowledge of the player’s characteristics in terms of different aspects and at different times of the season is needed. While the anthropometric and physical characteristics of men’s sports teams have been extensively studied, research on women’s basketball and volleyball is scarce. (1) Purpose: This study aims to contribute data about the anthropometric and physical characteristics of female basketball and volleyball players from elite women’s teams (age: 24.3 ± 2.7 years; playing experience: 14.825 ± 2.8 years) (n = 23) with a two-fold objective: (1) to describe and compare the anthropometric characteristics of these two disciplines; and (2) to identify possible differences in various parameters of sports performance depending on the discipline. (2) Methods: The anthropometric profile includes the measurements recommended by the International Society for the Advancement of Kinanthropometry; the performance tests described aerobic and anaerobic power exercises. (3) Results: The overall somatotype of the players was moderate mesomorphic and low endomorphic (5.107–3.046–1.883). Statistical differences were found between the improvement of the physical performance level of female basketball players (77%) and female volleyball players (10%) from the first to the last measurement, with better results in most of the performance tests (p < 0.05). The sum of skinfolds was higher in female basketball players (p > 0.05). The percentage of fat-free mass correlated with improvements in lower body strength. (4) Conclusion: Lean body mass is an important predictor of exercise performance intensity. Excess fat mass is detrimental to the development of strength and endurance.

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Section: Discussionsupporting

confidence: 53%

Comparison of Sports Performance and Kinanthropometric Profiles of Elite Female Basketball and Volleyball Players over the Course of a Competitive Season

2023

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“…However, we observed that the holistic typology of prakriti might also be associated with cognitive performance. While studies[ 31 32 ] have shown a relationship between somatic and prakriti body types, there is a scarcity of research on cognitive and motor function utilizing the two most generally used typologies, which represent diametrically opposed schools of thought.…”

Section: Discussionmentioning

confidence: 99%

“…This was the fundamental weakness of the research. Konjengbam et al .,[ 31 ] used a set of 41 features to delineate the prakriti types of healthy individuals. Rotti et al .,[ 36 ] used visual, tactile, vocal features, movement, and gait characteristics, and dietary and lifestyle-related parameters in the identification of prakriti types.…”

Section: Discussionmentioning

confidence: 99%

Using traditional typologies to understand posture movement and cognitive performance - A cross sectional study

Gupta¹,

Garg²,

Singh³

2022

Int J Yoga

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“…26 In this situation, the confidence level is 95% and the μα is 1.96. According to reports of anthropometric measurement, 27,28 a 5% margin of error is acceptable. When it is 5%, the minimum sample size required for the experiment was calculated as shown in Table 5.…”

Section: Methodsmentioning

confidence: 99%

Selection of breast features for young women in northwestern China based on the random forest algorithm

Zhou

Mao

Zhang

et al. 2021

Textile Research Journal

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In the research of breast morphology, numerous breast features are measured, whereas only a few parameters are adopted for classification. Therefore, how to extract the key variables from the multi-dimensional features in a rational way is an issue that is focused upon. This study aimed to reduce the complexity of the dimensionality reduction for further improving the objectivity and interpretability of the selected breast features. Since the random forest (RF) algorithm can quantify the feature importance during training, the method was adopted to determine the optimal breast features for classification and recognition in this paper. Firstly, the anthropometric data of 360 females from northwestern China aged from 19 to 27 years were measured by non-contact three-dimensional body scanning technology and the contact manual measurement method. Then, the k-means clustering was applied to categorize breast shapes, and the RF algorithm was utilized to quantify and rank the importance of 25 breast features. Finally, to verify the availability of the RF algorithm on breast feature selection, the t-distributed stochastic neighbor embedding method was adopted to visualize the distribution of breast shape clusters into two dimensions. Meanwhile, four neural networks were determined to recognize the breast morphology. The results demonstrate that fewer breast features can effectively increase the accuracy of breast shape classification and recognition. The best performance of breast shape classification and recognition is obtained when the number of breast features is 13. In this case, the average Hamming loss of four neural networks is the smallest (0.1136). Interestingly, the bust circumference and the horizontal curve of breasts across the bust points are found to be the most important of the 25 breast features in this paper. The importance of the breast curve features is higher than that of the breast cross-sectional features, while the breast positioning features have the lowest importance. Meanwhile, the RF algorithm is verified to be more effective than traditional dimensionality reduction methods, such as principal component analysis, hierarchical clustering, and recursive feature elimination. The approach developed in this paper can be generalized to the dimensionality reduction of other body morphology.

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Correlation of body composition parameters and anthropometric somatotypes with Prakriti body types among the Meitei adults of Manipur, India

Cited by 7 publications

References 13 publications

Comparison of Sports Performance and Kinanthropometric Profiles of Elite Female Basketball and Volleyball Players over the Course of a Competitive Season

Comparison of Sports Performance and Kinanthropometric Profiles of Elite Female Basketball and Volleyball Players over the Course of a Competitive Season

Using traditional typologies to understand posture movement and cognitive performance - A cross sectional study

Selection of breast features for young women in northwestern China based on the random forest algorithm

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