Camera-based objective measures of Parkinson’s disease gait features
| Autor: | Svitlana Zinger, Bastiaan R. Bloem, Jannis van Kersbergen, Hanna M Röhling, Sebastian Mansow-Model, Nicolien M. van der Kolk, Nienke M. de Vries, Merel M. van Gilst, Sebastiaan Overeem, Karen Otte |
|---|---|
| Přispěvatelé: | Electrical Engineering, Signal Processing Systems, Eindhoven MedTech Innovation Center, Biomedical Diagnostics Lab, Center for Care & Cure Technology Eindhoven, EAISI Health |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Science (General) Parkinson's disease Movement disorders QH301-705.5 Significant group Pilot Projects General Biochemistry Genetics and Molecular Biology Q1-390 All institutes and research themes of the Radboud University Medical Center Gait (human) Physical medicine and rehabilitation Rating scale Neurologic medicine Humans Gait Disorders Biology (General) Gait Gait Disorders Neurologic business.industry Parkinson Disease/diagnosis Symptom severity Parkinson Disease Neurodegenerative Diseases General Medicine Stride length Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3] Kinect TUG-test medicine.disease Walking Speed Preferred walking speed Research Note Parkinson’s disease Medicine medicine.symptom business |
| Zdroj: | BMC Research Notes BMC Research Notes, 14 BMC Research Notes, 14, 1 BMC Research Notes, Vol 14, Iss 1, Pp 1-6 (2021) BMC Research Notes, 14:329. BioMed Central |
| ISSN: | 1756-0500 |
| DOI: | 10.1186/s13104-021-05744-z |
| Popis: | Objective Parkinson’s disease is a common, age-related, neurodegenerative disease, affecting gait and other motor functions. Technological developments in consumer imaging are starting to provide high-quality, affordable tools for home-based diagnosis and monitoring. This pilot study aims to investigate whether a consumer depth camera can capture changes in gait features of Parkinson’s patients. The dataset consisted of 19 patients (tested in both a practically defined OFF phase and ON phase) and 8 controls, who performed the “Timed-Up-and-Go” test multiple times while being recorded with the Microsoft Kinect V2 sensor. Camera-derived features were step length, average walking speed and mediolateral sway. Motor signs were assessed clinically using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale. Results We found significant group differences between patients and controls for step length and average walking speed, showing the ability to detect Parkinson’s features. However, there were no differences between the ON and OFF medication state, so further developments are needed to allow for detection of small intra-individual changes in symptom severity. |
| Databáze: | OpenAIRE |
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