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Park-MOVE - fNIRS study of complex walking in Parkinson's disease

https://doi.org/10.48723/whpy-9662
Data availability: The participants of this study did not give written consent for their data to be shared publicly, so due to the sensitive nature of the research the data is not available. This dataset contains data collected between 2021 and 2023 for the Park-MOVE project. This project aims to explore brain activity during complex walking tasks involving a combination of motor and cognitive skills. The aim is to study the effects of aging and neurological disease on the performance and neural correlates of these tasks, using non-invasive measures of brain activity with functional near infrared spectroscopy, fNIRS, and advanced gait analysis methods. In addition, this dataset contains brain activity measured with fNIRS during rest for a subset of participants, i.e., resting-state measurements. Data is collected from younger healthy adults (YA), older healthy adults (OA) and people with Parkinson's disease (PD). In this dataset, there is data from 42 YA, 49 OA, and 42 PD. The dataset contains the following types of data: - fNIRS data - Clinical data - Questionnaire data - Inertial measurement unit (IMU) data - Walking protocol task performance data - Neuropsychological test battery data See project_overview.md for an overview of data. Each type of data has a detailed README file detailing how data has been processed. Most of the data is stored in CSV format and can be read by any program. The fNIRS data is stored in the BIDS and SNIRF standard formats. Gait parameters calculated from IMU data are stored in CSV format, but raw data is also available in the Apache Parquet format, which can be read using e.g. the Pandas Python library. Version 1: original version Version 2: Data corrected: Acceleration and de-acceleration phases removed from IMU parameters. Data added: Addition of resting-state data. Data removed: One participant excluded. Time period investigated: added 2024-02-20-2024-09-24
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Documentation files

Citation and access

Data access level:

Creator/​Principal investigator(s):

Research principal:

Principal's reference number:

  • 2020-03059

Data contains personal data:

Yes

Type of personal data:

Health data, medical data

Code key exists:

Yes

Sensitive personal data:

Yes

Citation:

Language:

Method and outcome

Unit of analysis:

Population:

Healthy adults, Parkinson's disease

Time method:

Study design:

  • Cross-sectional study
  • Observational study

Sampling procedure:

Description of sampling:

Availability sampling via recruitment advertisements in patient groups and other networks.

Time period(s) investigated:

Number of individuals/​objects:

132

Data format/​data structure:

Geographic coverage

Geographic location:

Administrative information

Responsible department/​unit:

Department of Neurobiology, Care Sciences and Society [H1]

Ethical Review

Reviewer:

Registration number:

2020-03059

Funding

Funding agency:

Award number:

2022-00636_VR

Award title:

Park-MOVE: Moving towards personalized rehabilitation for Parkinson’s disease informed by diversity, exercise responders and brain activity during motion.

Funding information:

Life means combining motor-cognitive skills, e.g., walking, talking and navigating. Aging or neurological diseases, e.g., Parkinson’s disease (PD) compromises these skills needed for an independent life. It is uncertain which brain alterations lead to these difficulties and how to target these heterogenous motor-cognitive difficulties. Current treatments apply a "one-size-fits-all" approach, which needs to evolve towards personalized rehabilitation, reaching beyond a simple adaption to disease severity.Our multimodal project combines physiotherapy, neurology, psychology and neuroimaging to characterize motor-cognitive skills during complex walking, identify underlying brain alterations and subtype PD to inform a novel exercise approach for people with PD. This 5 years proposal has 4 stages: 1) Exploring brain alterations and links to the motor-cognitive skills in healthy and PD 2) PD subtyping using neuroimaging, motor, cognitive and clinical data 3) Characterization of exercise responsiveness in PD and 4) Development and testing of a personalized motor-cognitive exercise program. We combine novel techniques for data collection with in-depth analysis of existing data (EXPANd trial). The results will have an immediate application and clinical relevance for personalized rehabilitation in older and PD. There is no cure for PD yet, thus positive findings would revolutionize treatment, giving new hope to patients for a life with improved health, independence and higher quality.

Topic and keywords

Swedish Standard Classification of Research Subjects 2025:

Keywords:

Relations

Is supplemented by:

Clinical trials registration

Is supplemented by:

Park-MOVE fNIRS data preparation

Is supplemented by:

fNIRS validation study

Publications

Citation:

Kvist, A., Bezuidenhout, L., Johansson, H., Albrecht, F., Conradsson, D., & Franzen, E. (2024). Validation of fNIRS measurement of executive demand during walking with and without dual-task in younger and older adults and people with Parkinson’s disease. In NEUROIMAGE-CLINICAL (Vol. 43, pp. 103637–103637). https://doi.org/10.1016/j.nicl.2024.103637

SwePub:

oai:swepub.ki.se:874603

Citation:

Kvist, A., Peterson, D., Bezuidenhout, L., Johansson, H., Albrecht, F., Ekman, U., Conradsson, D., & Franzen, E. (2026). Exploring gait automaticity and prefrontal brain activity during single and dual-task walking in aging and Parkinson’s disease. In JOURNAL OF NEUROENGINEERING AND REHABILITATION (Vol. 23, Issue 1). https://doi.org/10.1186/s12984-025-01864-w

SwePub:

oai:swepub.ki.se:1090286

Contact

Metadata

Versions

Version:

2

DOI:

https://doi.org/10.48723/whpy-9662

  • Data corrected:

    Acceleration and de-acceleration phases removed from IMU parameters.

  • Data added:

    Addition of resting-state data.

  • Data removed:

    One participant excluded.

Published:

Version:

1

DOI:

https://doi.org/10.48723/vscr-eq07

Published:

doris
ki
Version 2 published: