Automated Anthropometric Analysis for Personalized Workspace Optimisation

This paper presents a novel pipeline for automated anthropometric analysis aimed at personalized workspace optimization. We leverage MediaPipe to extract eight key body dimensions from individual images: Sitting Height, Sitting Eye Height, Elbow to Fingertip, Elbow to Seat Height, Knee to Foot Length, Back to Elbow Length, Shoulder Width, and Hip Width. We constructed a dataset of calibrated images to train and validate our system. The developed pipeline achieves 85% accuracy in extracting these measurements. Subsequently, we generate a 3D model of the user's workspace in Blender, providing dimensional feedback and visual ergonomic assessments. This approach offers a practical and efficient solution for enhancing user comfort and productivity by enabling personalized workspace design.

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Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006173
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
Field-Weighted Citation Impact
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article

Automated Anthropometric Analysis for Personalized Workspace Optimisation

Sanjiv M. Narayan, Nidhi Singh, Nihaal Kuchangi, Neha Vemireddy et al.
AHFE international
Ergonomics and Musculoskeletal Disorders
article

Automated Anthropometric Analysis for Personalized Workspace Optimisation

Sanjiv M. Narayan, Nidhi Singh, Nihaal Kuchangi, Neha Vemireddy, Navya Govil
article en

Abstract

This paper presents a novel pipeline for automated anthropometric analysis aimed at personalized workspace optimization. We leverage MediaPipe to extract eight key body dimensions from individual images: Sitting Height, Sitting Eye Height, Elbow to Fingertip, Elbow to Seat Height, Knee to Foot Length, Back to Elbow Length, Shoulder Width, and Hip Width. We constructed a dataset of calibrated images to train and validate our system. The developed pipeline achieves 85% accuracy in extracting these measurements. Subsequently, we generate a 3D model of the user's workspace in Blender, providing dimensional feedback and visual ergonomic assessments. This approach offers a practical and efficient solution for enhancing user comfort and productivity by enabling personalized workspace design.

AHFE internationalVol. 170
Openalex Percentile: Top 83%
Ergonomics and Musculoskeletal Disorders
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