Automatic digital biometry analysis based on depth maps

Miguel Reyes, Albert Clapés, José Ramírez, Juan R. Revilla, Sergio Escalera

    Research output: Contribution to journalArticleResearchpeer-review

    13 Citations (Scopus)


    World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments. © 2013 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)1316-1325
    JournalComputers in Industry
    Issue number9
    Publication statusPublished - 1 Jan 2013


    • Anthropometric data
    • Depth maps
    • Gesture analysis
    • Multi-modal data fusion
    • Musculo-skeletal disorders
    • Posture analysis


    Dive into the research topics of 'Automatic digital biometry analysis based on depth maps'. Together they form a unique fingerprint.

    Cite this