Utilizing Additive Manufacturing for Economical Prosthetic Limb Prototyping:  A Guide from Regression Modelling

Adekunle Ibrahim Musa; Adebanjo  Oluwakayode Sukanmi; Folorunsho Uthman Oluwadamilare

doi:10.69650/ahstr.2024.2210

Authors

Adekunle Ibrahim Musa Department of Mechanical Engineering Olabisi Onabanjo University Ago Iwoye Ogun State-
Adebanjo Oluwakayode Sukanmi Department of Mechanical Engineering Olabisi Onabanjo University Ago Iwoye, Ibogun Campus Ogun State
Folorunsho Uthman Oluwadamilare Department of Mechanical Engineering Olabisi Onabanjo University Ago Iwoye, Ibogun Campus Ogun State

DOI:

https://doi.org/10.69650/ahstr.2024.2210

Keywords:

anthropometric, ergonomic, disability design: prosthetic limb, amputee

Abstract

This study investigated the development of a low-cost prosthetic limb using additive manufacturing techniques, guided by anthropometric data and regression modeling. Anthropometric measurements were collected from 250 healthy young adults to characterize limb dimensions. Statistical analysis revealed the mean, standard deviation, and range for right and left leg and elbow lengths. A regression model was formulated to estimate limb lengths based on these measurements. A robust regression model demonstrated a significant correlation (r = 0.993, r² = 0.986) between right limb measurements and corresponding left limb measurements, indicating that right leg and elbow lengths could accurately predict left side measurements. The derived regression equation (RLL = 2.253 + 0.959 LLL + 0.054 LEL) provides a practical tool for designing customized prosthetics. Utilizing 3D printing technology, these findings can enhance the production of tailored prosthetic limbs, improving comfort and functionality for users. The study recommends further validation across diverse populations, integration into clinical practices, and continued research and development supported by policy and funding initiatives. These steps will advance the accessibility and effectiveness of personalized prosthetic solutions.

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