Hyperkinetic movement disorders involuntary movements Hyperkinetic movement disorders involuntary movements
Conditions
Interventions
N.A.
Sponsors
Universitair Medisch Centrum Groningen
Eligibility
Age
2 Years to 64 Years
Inclusion criteria
Inclusion criteria: - >= 16 years of age. - Patients with a clinically confirmed diagnosis of one of the included single phenotypes (dystonia, tremor, myoclonus, tics, chorea, spasticity, ataxia) OR mixed phenotyping OR healthy controls. - For pediatric patients in part A and part B >= 6 years of age
Exclusion criteria
Exclusion criteria: - Other neurological conditions that lead to movement problems other than hyperkinetic movement disorders. - Other conditions that lead to impaired hand or arm function. - With regard to healthy subjects: no first degree family member of a patient with a hyperkinetic movement disorder. - Silver allergy - Pace-makers - For pediatric patients: not able to follow instructions
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| During a single hospital visit or at an external location, participants will be questioned about clinical parameters, such as age at onset, will fill out several questionnaires on non-motor symptom severity, and will be asked to perform several simple motor tasks with the arms. While executing these tasks, participants will be recorded using 3D video, motion sensors, and muscle activity sensors. Expert-based phenotype classification by three experts, based on the video recordings and clinical parameters, will serve as input for machine learning. Phenotype specific data clusters of the clinical parameters, 3D video, motion sensors, muscle activity sensors, FDG-PET imaging, fMRI, and machine learning will be used to develop CAD models able to differentiate the movement disorders. Algorithms, data quality assessment, discriminant feature design, classifier training and validation will be applied using these data clusters in machine learning. | — |
Secondary
| Measure | Time frame |
|---|---|
| Furthermore, the discrepancies between the phenotyping of the CAD-tool and the clinical experts will be analyzed to improve the CAD-tool and gain further understanding about clinical judgement. Moreover, the pathophysiological brain process of dystonia, tremor, and myoclonus will be analyzed by linking phenotypes to patterns of regional changes in brain function. Additionally, it will be analyzed whether regional change patterns in brain function are phenotype- of genotype-specific in myoclonus-dystonia. | — |
Countries
Netherlands
Contacts
Public ContactI. Tuitert
Universitair Medisch Centrum Groningen
Outcome results
None listed