KINECAL: A Dataset for Falls-Risk Assessment and Balance Impairment Analysis

Autor: Sean Maudsley-Barton, Moi Hoon Yap
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Scientific Data, Vol 10, Iss 1, Pp 1-15 (2023)
Druh dokumentu: article
ISSN: 2052-4463
75060868
DOI: 10.1038/s41597-023-02375-w
Popis: Abstract The field of human action recognition has made great strides in recent years, much helped by the availability of a wide variety of datasets that use Kinect to record human movement. Conversely, progress towards the use of Kinect in clinical practice has been hampered by the lack of appropriate data. In particular, datasets that contain clinically significant movements and appropriate metadata. This paper proposes a dataset to address this issue, namely KINECAL. It contains the recordings of 90 individuals carrying out 11 movements, commonly used in the clinical assessment of balance. The dataset contains relevant metadata, including clinical labelling, falls history labelling and postural sway metrics. KINECAL should be of interest to researchers interested in the clinical use of motion capture and motion analysis.
Databáze: Directory of Open Access Journals
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