phat 21(26): e4

Research Article

Non-obtrusive 3d body tracking for automated mobility assessment in independently living older persons. Results of a pilot trial

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  • @ARTICLE{10.4108/eai.4-3-2021.168863,
        author={J. Lumetzberger and T. M\'{y}nzer and M. Kampel},
        title={Non-obtrusive 3d body tracking for automated mobility assessment in independently living older persons. Results of a pilot trial},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={7},
        number={26},
        publisher={EAI},
        journal_a={PHAT},
        year={2021},
        month={3},
        keywords={gait speed, depth data, non-obtrusive mobility assessment, AAL, physiotherapist, privacy},
        doi={10.4108/eai.4-3-2021.168863}
    }
    
  • J. Lumetzberger
    T. Münzer
    M. Kampel
    Year: 2021
    Non-obtrusive 3d body tracking for automated mobility assessment in independently living older persons. Results of a pilot trial
    PHAT
    EAI
    DOI: 10.4108/eai.4-3-2021.168863
J. Lumetzberger1,*, T. Münzer2, M. Kampel1
  • 1: Computer Vision Lab, Vienna University of Technology, Favoritenstr. 9, 1040 Vienna, Austria
  • 2: Geriatrische Klinik St. Gallen, Rorschacher Str. 94, 9000 St. Gallen, Switzerland
*Contact email: jennifer.lumetzberger@tuwien.ac.at

Abstract

INTRODUCTION: With rising age, functional deficit and frequent falls may lead to long-term care admission. Mobility assessment tests can detect fall risk and may induce interventions that prevent a fall.

OBJECTIVES: To assess mobility of older persons using real time data and to compare these data with the mobility assessment of physiotherapists.

METHODS: 20 older people aged 74±5 (mean ± SD) were monitored over 10 months to investigate the performance of an automated mobility tracker. Physiotherapists performed periodic mobility assessments. Annotated 3d recordings served as ground truth data.

RESULTS: High correlation (r=0.684) of annotated and tracked gait speed was found. The mean absolute error is 0.16 m/s.

CONCLUSION: 3D mobility trackers can be used to collect long-term mobility data. Since changes in mobility might indicate functional decline, long-term tracking allows to react to changes in mobility. Such a technology may have essential medical and social value.