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Morgan C, Tonkin EL, Masullo A, Jovan F, Sikdar A, Khaire P, Mirmehdi M, McConville R, Tourte GJL, Whone A, Craddock I. A multimodal dataset of real world mobility activities in Parkinson's disease. Sci Data 2023; 10:918. [PMID: 38123584 PMCID: PMC10733419 DOI: 10.1038/s41597-023-02663-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 10/19/2023] [Indexed: 12/23/2023] Open
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.
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Affiliation(s)
- Catherine Morgan
- Movement Disorders Group, Bristol Brain Centre, North Bristol NHS Trust, Southmead Hospital, Southmead Road, Bristol, BS10 5NB, UK
- Translational Health Sciences, University of Bristol, 5 Tyndall Ave, Bristol, BS8 1UD, UK
| | - Emma L Tonkin
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK.
| | - Alessandro Masullo
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
| | - Ferdian Jovan
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
- School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, UK
| | - Arindam Sikdar
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
- Edge Hill University, Ormskirk, UK
| | - Pushpajit Khaire
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
- Datta Meghe Institute of Higher Education and Research, Wardha, India
| | - Majid Mirmehdi
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
| | - Ryan McConville
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
| | - Gregory J L Tourte
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
- Advanced Research Computing, University of Oxford, Oxford, UK
| | - Alan Whone
- Movement Disorders Group, Bristol Brain Centre, North Bristol NHS Trust, Southmead Hospital, Southmead Road, Bristol, BS10 5NB, UK
- Translational Health Sciences, University of Bristol, 5 Tyndall Ave, Bristol, BS8 1UD, UK
| | - Ian Craddock
- Faculty of Engineering, University of Bristol, Digital Health Offices, 1 Cathedral Square, Bristol, BS1 5DD, UK
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