ArticleScientific data2022
Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Combining magnetic resonance imaging and evoked potentials enhances machine learning prediction of multiple sclerosis disability worsening.Frontiers in immunology · 2026Article
- Empowering Health Care Actors to Contribute to the Implementation of Health Data Integration Platforms: Retrospective of the medEmotion Project.Journal of medical Internet research · 2025Article
- The role of trustworthy and reliable AI for multiple sclerosis.Frontiers in digital health · 2025Article
- Patient level dataset to study the effect of COVID-19 in people with Multiple Sclerosis.Scientific data · 2024Article
- Transcranial Magnetic Stimulation Measures, Pyramidal Score on Expanded Disability Status Scale and Magnetic Resonance Imaging of Corticospinal Tract in Multiple Sclerosis.Bioengineering (Basel, Switzerland) · 2023Article
- Assessment of Motor Evoked Potentials in Multiple Sclerosis.Sensors (Basel, Switzerland) · 2023Review
- Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset.Scientific data · 2022Article
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Authors and funding
5 authors.
Funding
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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.
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