health life sciences medicine
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 using 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 and postural sway metrics. In addition, the recordings were made in both the lab and in informal settings.
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Creative Commons Zero 1.0 Universal Public Domain Dedication
https://doi.org/10.13026/vvkp-ct80
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KINECAL was accessed on DATE from https://registry.opendata.aws/kinecal.
arn:aws:s3:::physionet-open/kinecal/us-east-1aws s3 ls --no-sign-request s3://physionet-open/kinecal/