Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37531
Title: Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset
Authors: YPERMAN, Jan 
POPESCU, Veronica 
VAN WIJMEERSCH, Bart 
BECKER, Thijs 
PEETERS, Liesbet 
Issue Date: 2022
Publisher: NATURE PORTFOLIO
Source: Scientific Data, 9 (1) (Art N° 207)
Abstract: Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. Through the demyelinating and axonal pathology of MS, the signal conduction in the central nervous system is affected. Evoked potential measurements allow clinicians to monitor this process and can be used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements, in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100 milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset contains 5586 visits of 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000 MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used to explore the role of evoked potentials in MS research and patient care. It may also be used as a benchmark for time series analysis and predictive modelling.
Notes: Peeters, LM (corresponding author), Hasselt Univ, Biomed Res Inst BIOMED, B-3500 Hasselt, Belgium.; Peeters, LM (corresponding author), Hasselt Univ, Data Sci Inst DSI, B-3500 Hasselt, Belgium.; Peeters, LM (corresponding author), Hasselt Univ, Univ MS Ctr UMSC, B-3500 Hasselt, Belgium.
liesbet.peeters@uhasselt.be
Document URI: http://hdl.handle.net/1942/37531
e-ISSN: 2052-4463
DOI: 10.1038/s41597-022-01335-0
ISI #: WOS:000796510400002
Rights: Te Author(s) 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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