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 (REal-world Mobility Activities in Parkinson’s disease), a human rater-labelled dataset collected in a home-like setting. It includes people with and without PD doing sit-to-stand transitions and turns in gait. These discrete activities are captured from periods of free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their activities are labelled as being “on” or “off” medications. Accelerometry from wrist-worn wearables and skeleton pose video data is included. We present an open dataset, where the data is coarsened to reduce re-identifiability, and a controlled dataset available on application which contains more refined data. A use-case for the data to estimate sit-to-stand speed and duration is illustrated.
Original languageEnglish
Article number918
Pages (from-to)1-18
Number of pages18
JournalScientific data
Issue number1
Early online date20 Dec 2023
Publication statusPublished - 20 Dec 2023


  • multimodal dataset
  • mobility activities
  • real world
  • Parkinson’s disease
  • Parkinson’s
  • neurodegenerative disorder
  • Technological tools
  • REMAP (REal-world Mobility Activities in Parkinson’s disease)
  • Gait
  • Humans
  • Time
  • Parkinson Disease
  • Accelerometry


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