AIMC Topic: Movement Disorders

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Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Computers in biology and medicine
Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurological diseases, adherence to medication regimens can be assessed by observing movement patterns. Howeve...

Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging.

Human brain mapping
Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classificati...

Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute post-stroke patients. The system permits synchronized cortical and kinematic measures by integrating high-resolution EEG, passive robotic device and Vir...

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques.

Cerebral cortex (New York, N.Y. : 1991)
Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associate...

Explainable machine learning for movement disorders - Classification of tremor and myoclonus.

Computers in biology and medicine
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.

[Research status of lower limb exoskeleton rehabilitation robot].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Lower limb exoskeleton rehabilitation robots are used to improve or restore the walking and movement ability of people with lower limb movement disorders. However, the required functions for patients differ based on various diseases. For example, pat...

Estimating infant upper extremities motion with an RGB-D camera and markerless deep neural network tracking: A validation study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantitative biomarkers of infant motion may be predictive of the development of movement disorders. This study presents and validates a low cost, markerless motion tracking method for the estimation of upper body kinematics of infants from which pro...

[NEW OPPORTUNITIES IN NEURO-REHABILITATION: ROBOT MEDIATED THERAPY IN CONDITONS POST CENTRAL NERVOUS SYSTEM IMPAIRMENTS].

Ideggyogyaszati szemle
Decreasing the often-seen multiple disabilities as a consequence of central nervous system impairments requires broadening of the tools of rehabilitation. A promising opportunity for this purpose is the application of physiotherapy robots. The develo...