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Anthropometric Data Collection and Analysis Model

EasyChair Preprint 14363

16 pagesDate: August 9, 2024

Abstract

Anthropometric data collection and analysis serve as a cornerstone in various fields, including ergonomics, biomechanics, healthcare, and product design. This model provides a systematic approach to acquiring, processing, and interpreting anthropometric measurements to enhance precision and applicability. The model emphasizes the integration of advanced technologies such as 3D body scanning, machine learning algorithms, and big data analytics to overcome the limitations of traditional methods. By incorporating diverse demographic variables—such as age, gender, ethnicity, and occupation—the model aims to deliver a comprehensive dataset that reflects the variability in human body dimensions. The analysis phase focuses on identifying key patterns, trends, and correlations, which are essential for designing products, workspaces, and health interventions tailored to specific populations. The model also includes a feedback loop to refine data collection protocols and ensure continuous improvement. Ultimately, this approach supports the creation of more inclusive and effective solutions across multiple domains.

Keyphrases: 1. **Anthropometry**, 10. **Measurement Tools**, 11. **Ethical Considerations**, 12. **Sample Size**, 13. **Data Preprocessing**, 14. **Statistical Analysis**, 15. **Data Representation**, 16. **3D Body Scanning**, 17. **Model Validation**, 18. **Design Parameters**, 19. **Customizable Furniture**, 2. **Ergonomics**, 20. **Educational Settings**, 3. **Data Collection**, 4. **Anthropometric Measurements**, 5. **Ergonomic Furniture Design**, 6. **School Furniture**, 7. **Data Analysis**, 8. **Cross-Validation**, 9. **Multivariate Analysis**

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:14363,
  author    = {Wayzman Kolawole},
  title     = {Anthropometric Data Collection and Analysis Model},
  howpublished = {EasyChair Preprint 14363},
  year      = {EasyChair, 2024}}
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