Automatic digital biometry analysis based on depth maps

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

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

13 Citations (Scopus)

Abstract

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.

Original languageEnglish
JournalComputers in Industry
Volume64
Issue number9
Pages (from-to)1316-1325
Number of pages10
ISSN0166-3615
DOIs
Publication statusPublished - Dec 2013
Externally publishedYes

Bibliographical note

Funding Information:
This work is partly supported by projects IMSERSO-Ministerio de Sanidad 2011 Ref. MEDIMINDER , and RECERCAIXA 2011 Ref. REMEDI .

Keywords

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

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