In a pioneering study, from the Expertise Centre for Movement Disorders in Groningen, Machine Learning, a core area of artificial intelligence (AI), is successfully used for the first time to distinguish different types of movement disorders from each other. The Next Move in Movement Disorders (NEMO) project, led by neurologist Prof Marina de Koning-Tijssen, is the result of an innovative collaboration with the Bernoulli Institute at the University of Groningen (RUG). This study is published in the scientific journal Computers in Biology and Medicine.
Distinction between tremor and myoclonus
The first result from the project focuses on the distinction between tremor and myoclonus, two types of involuntary movements that are often confused because of their similar symptoms. Tremor is an involuntary movement often associated with common diseases such as essential tremor and Parkinson's disease, while myoclonus is characterised by sudden, short muscle contractions that can result from a wide range of different neurological conditions. Elina van den Brandhof, researcher within the NEMO project shows that tremor and myoclonus can be very well distinguished with the new method. The difference in diagnosis is crucial for treatment, as approaches for these disorders vary widely.
Recognizing symptoms and confirm diagnosis
Movement disorders often show overlapping symptoms, making it difficult for doctors to make the correct diagnosis. Patients may also experience multiple movement disorders at the same time, further complicating the diagnostic process. The new method makes it possible to distinguish these types of movement disorders from each other while supporting the doctor in the diagnosis made. "The application of intelligent systems allows us to recognize and confirm diagnoses faster. This opens the door to more targeted treatments and better care for our patients," said Prof Marina de Koning-Tijssen, neurologist and head of the UMCG Expertise Centre for Movement Disorders in Groningen.
Improving medical diagnoses towards personalized medical care
The study, published for the first time in a leading scientific journal, offers new perspectives for neurology. Intelligent systems can process increasingly complex data, significantly improving the speed and accuracy of medical diagnoses. This is an important step towards personalised care for people with movement disorders, where treatments can be better tailored to patients' specific needs.
The collaboration between the Centre of Expertise and the Bernoulli Institute of the University of Groningen marks an important milestone in the use of AI in medical science. The researchers expect that the technology will eventually be more widely applicable in neurology and other medical fields. "This breakthrough is a major step forward. The use of intelligent data analysis via machine learning in neurology offers not only scientific advances, but also concrete benefits for clinical practice and a better understanding of diseases," says Professor Michael Biehl of the Bernoulli Institute.
With this innovative development, the Expertise Centre for Movement Disorders in Groningen confirms its international leading role in the field of movement disorders and computer-assisted medical care.
Computers in Biology and Medicine
10.1016/j.compbiomed.2025.110180
Experimental study
People
Explainable machine learning for movement disorders - Classification of tremor and myoclonus
8-May-2025