Winner of the Machine Learning Challenge 2021

Tim Segger and Cedric Vadder (middle of photo) implemented high precision models to distinguish Parkinson’s Disease from other movement disorders. Their model performed best and most robust in the project seminar at the Department of Computer Science, University of Münster (Accuracy >82%, SD <0.02). Congratulations!

Paper on Sensor Validation & Machine Learning published

Smartwatches are capable of measuring very subtle tremor phenomena almost at the level of seismometers! Our Open Access Paper on sensor validation and preliminary Machine Learning results is published by Sensors, the leading open access journal on the science and technology of sensors. The work resulted from a close collaboration with the Institute of Geophysics.…
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More than 500 participants measured

Though the recruitment was persistently limited during the pandemic, we could still carry on to assess further participants with our new system (see figure). The App-based data capture und continuous data quality monitoring ensured 100% data completeness. We are going to soon submit further preliminary data analyses results to a special issue by Sensors.

Eight new students participating in intense Machine Learning Course for Winter term 2020/2021

The course is a 10-15 ECTS points project seminar for Computer Science students at the University of Münster. This time, we are focusing on promising Methods of Ensemble Learning with Stacking and Deep Neural Networks. We are looking forward for new interesting algorithms and of course the best-performing team to beat accuracies from last course.

Winner of the Machine Learning Challenge 2020

Our students Luisa Beerboom and Alexander Leifhelm implemented high precision models classifying Parkinson’s disease vs other movement disorders and healthy samples. Their model performed best and most robust in our intense project seminar at the Department of Computer Science, University of Münster (Accuracy >80%, SD <0.03). Congratulations!

Recruitment starts again with new system features

Since this week, our study continues to measure new participants. The system can now capture spiral drawings, speech and voice analyses. The update received ethical approval. We are excited to to search for new biomarkers in Parkinson’s disease and other Movement Disorders.

Recruitment paused, 433 participants measured.

Since March 2020 our study is not recruiting to reduce the spread of the virus. However, our site is experiencing a significant reduction of Covid cases on intensive care units. Study reactivation is soon, we will keep you informed. We can gladly confirm that we had regular recruitment until March and provide our most current…
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MIE 2020 conference cancelled

The ongoing Covid-19 pandemic affected all scientific conferences. Naturally, to reduce spreading of the virus, the MIE 2020 Conference was cancelled. Our planned talk on our study with interim analyses on our Machine Learning pipeline and diagnostic accuracy is still going to be published under the Conference proceedings and indexed in Pubmed. More information to…
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More than 400 participants

Our study has now measured >400 participants, with 239 cases of Parkinson’s disease. 100% data completeness for each case!


Our submission entitled “The Smart Device System for Movement Disorders: Preliminary Machine Learning Results from an Observational Study” was accepted as Full Paper in the Medical Informatics Europe Conference 2020 in Geneva. The paper presents details of our Machine Learning Pipeline and promising interim results on diagnostic accuracy of our system. See you in Geneva…
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