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Title Distinguishing between hyperkinetic movement disorders: easy for the expert?
Keywords myoclonus Dystonia tremor
Researchers prof. dr. M.A.J. de Koning-Tijssen
Dr. A.M.M. van der Stouwe
dr. I. Tuitert
Nature of the research The student will participate in different aspect of the NEMO study (the NExt move in MOvement disorders), organised within the Expertise Centre Movement Disorders Groningen. This is a large study in patients with hyperkinetic movement disorders, such as tremor, dystonia and myoclonus, where we aim to develop a computer aided diagnosis tool to help clinicians to make the correct diagnosis. A team of neurologists, movement scientists, computer scientists and several PhD students are involved, and the student will become a part of this team. Data collection for this study is in full swing, and the student will get to work in a well organised team while also having clear individual tasks (see the workplan below). The student is encouraged to visit our groups weekly online and offline meetings, such as the movement disorders video’s meetings, work in progress meetings, the department of neurology’s research meetings and the journal club.
Fields of study neurology
Background / introduction
The hyperkinetic movement disorders myoclonus, dystonia, tremor, chorea and tics are all characterised by excessive, involuntary movements. In a patient presenting with such a disorder, it is crucial to classify the movement disorder phenotype quickly and correctly, because the phenotype classification is the basis for decisions about diagnostic testing and treatment. While phenotype recognition is clearly important, unfortunately correct classification is difficult in many patients. This problem delays proper diagnosis and the start of the correct treatment.
To improve the classification of hyperkinetic movement disorders we set up the current study, Next Move in Movement Disorders (NEMO). Our aim is to combine electromyography (EMG), motion sensors, and 3D video with machine learning to develop a computer aided classification tool for hyperkinetic movement disorders, which will help health care professionals establish the movement disorders phenotype. To enable inclusion, patient data will be reviewed by a blinded (inter)national panel of experts to assess their phenotype. This procedure serves as our “gold standard”, but also allows us to investigate how often experts agree and disagree about movement disorders classification.
Research question / problem definition
- What is the interrater agreement on hyperkinetic movement disorders patient’s classification by blinded experts, based on:
1) video;
2) video and clinical information (history and neurological examination);
3) video, clinical information and diagnostic test information (neurophysiology, neuroimaging, genetics)?
- How certain do they feel about their classification?
- Which type of information is most likely to change their mind?
Workplan
Firstly, the student will get acquainted with the study protocol and patient population. Patients participate in a movement registration with electromyography (EMG), accelerometry and 3D and 2D video recordings. Our team will take him/her on board and train them to participate in the data collection measurements. These measurements are always performed by a two people, so the student works in collaboration with an experienced investigator.
Secondly, the student will start to extract relevant clinical and diagnostic information from the patient files, to present to the experts. This will be done under supervision so the student can ask any questions they like. Experts will be presented with information and videos in a secure online environment and report back via this same secure system. Currently, the first expert assessments are piloted and the results of the first patients will come in soon, ensuring that enough data will be available to draw meaningful conclusions by the end of the project.
References
The next move in movement disorders (NEMO): developing a computer aided classification tool for hyperkinetic movement disorders. A.M.M. van der Stouwe, I. Tuitert, I. Giotis1, J. Calon1, R. Gannamani, J.R. Dalenberg, S. van der Veen, M.R. Klamer, A.C. Telea, M.A.J. Tijssen. BMJ Open 2021.

Clinical decision-making in functional and hyperkinetic movement disorders. S.M.A. van der Salm, A.F. van Rootselaar, D.C. Cath, R.J. de Haan, J.H.T.M. Koelman, M.A.J. Tijssen. Neurology 2017.
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