Non-obtrusive 3d body tracking for automated mobility assessment in independently living older persons. Results of a pilot trial
DOI:
https://doi.org/10.4108/eai.4-3-2021.168863Keywords:
gait speed, depth data, non-obtrusive mobility assessment, AAL, physiotherapist, privacyAbstract
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.
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Copyright (c) 2022 EAI Endorsed Transactions on Pervasive Health and Technology
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