Abstract
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 language | English |
|---|---|
| Article number | 918 |
| Number of pages | 18 |
| Journal | Scientific Data |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 20 Dec 2023 |
Bibliographical note
Funding Information:We gratefully acknowledge the study participants for their time and efforts in participating in this research and the local Parkinson’s and Other Movement Disorders Health Integration Team (Patient and Public Involvement Group) for their assistance in study design. This work was supported by the SPHERE Next Steps Project funded by the EPSRC, [Grant EP/R005273/1]; and the Elizabeth Blackwell Institute for Health Research, University of Bristol and the Wellcome Trust Institutional Strategic Support Fund [grant code: 204813/Z/16/Z]; and by Cure Parkinson’s Trust [grant code AW021]; and by IXICO [grant code R101507-101]. Dr Jonathan de Pass and Mrs Georgina de Pass made a charitable donation to the University of Bristol through the Development and Alumni Relations Office to support research into Parkinson’s Disease. The funding pays for the salary of CM. We also acknowledge the hard work and dedication of our Research Data Service colleague Zosia Beckles.
Data Availability Statement
The code for 2D and 3D skeleton pose data generation and the use-case code evaluating STS speed is available here: https://github.com/ale152/SitToStandPD.
Access to Document
- Morgan_etal_SD_A_Multimodal_Dataset_VOR
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