REMAP Open dataset

Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor symptoms, such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP, a human rater-labelled dataset of REal-world Mobility Activities in Parkinson's disease including people with and without PD doing sit-to-stand transitions and turns in gait while living in a home setting. These discrete activities are captured from free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their events are labelled as being “on” or “off” medications. We include skeleton pose camera data. We present this open dataset, where the skeleton pose data is coarsened for anonymisation. We illustrate use-case code measuring sit-to-stand duration, tested on both coarsened and refined data. This is a sister dataset so our controlled dataset (available on application) where there is more refined skeleton pose data and accelerometry.

Complete download (zip, 351.4 MiB)

Alternative title REMAP Open: an open dataset of REal-world Mobility Activities in Parkinson's disease
Creator(s) Ian Craddock, Majid Mirmehdi, Emma Tonkin, Gregory Tourte, Alessandro Masullo, Ryan McConville, Alan Whone, Catherine Morgan, Ferdian Jovan, Arindam Sikdar, Pushpajit Khaire
Publication date 08 Sep 2023
Language eng
Publisher University of Bristol
Licence Creative Commons Attribution 4.0
Warranty Disclaimer of Warranties and Limitation of Liability
DOI 10.5523/bris.21h9f9e30v9cl2fapjggz4q1x7
Citation Ian Craddock, Majid Mirmehdi, Emma Tonkin, Gregory Tourte, Alessandro Masullo, Ryan McConville, Alan Whone, Catherine Morgan, Ferdian Jovan, Arindam Sikdar, Pushpajit Khaire (2023): REMAP Open dataset. https://doi.org/10.5523/bris.21h9f9e30v9cl2fapjggz4q1x7
Total size 351.4 MiB

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