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Movement Disorders

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Diagnostic value of a vision-based intelligent gait analyzer in screening for gait abnormalities.

Gait & posture
BACKGROUND: Early detection of gait abnormalities is critical for preventing severe injuries in future falls. The timed up and go (TUG) test is a commonly used clinical gait screening test; however, the interpretation of its results is limited to the...

Perception of yips among professional Japanese golfers: perspectives from a network modelled approach.

Scientific reports
'Yips' in golf is a complex spectrum of anxiety and movement-disorder that affects competitive sporting performance. With unclear etiology and high prevalence documented in western literature, the perception and management of this psycho-neuromuscula...

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...

A multi-stage transfer learning strategy for diagnosing a class of rare laryngeal movement disorders.

Computers in biology and medicine
BACKGROUND: It remains hard to directly apply deep learning-based methods to assist diagnosing essential tremor of voice (ETV) and abductor and adductor spasmodic dysphonia (ABSD and ADSD). One of the main challenges is that, as a class of rare laryn...

Automated Quantification of Eye Tics Using Computer Vision and Deep Learning Techniques.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Tourette syndrome (TS) tics are typically quantified using "paper and pencil" rating scales that are susceptible to factors that adversely impact validity. Video-based methods to more objectively quantify tics have been developed but are ...

Machine Learning Approaches to Identify Affected Brain Regions in Movement Disorders Using MRI Data: A Systematic Review and Diagnostic Meta-analysis.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Movement disorders such as Parkinson's disease are associated with structural and functional changes in specific brain regions. Advanced magnetic resonance imaging (MRI) techniques combined with machine learning (ML) are promising tools f...

Research on Monitoring Assistive Devices for Rehabilitation of Movement Disorders through Multi-Sensor Analysis Combined with Deep Learning.

Sensors (Basel, Switzerland)
This study aims to integrate a convolutional neural network (CNN) and the Random Forest Model into a rehabilitation assessment device to provide a comprehensive gait analysis in the evaluation of movement disorders to help physicians evaluate rehabil...

[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...

Automatic two-dimensional & three-dimensional video analysis with deep learning for movement disorders: A systematic review.

Artificial intelligence in medicine
The advent of computer vision technology and increased usage of video cameras in clinical settings have facilitated advancements in movement disorder analysis. This review investigated these advancements in terms of providing practical, low-cost solu...

Automated Sleep Detection in Movement Disorders Using Deep Brain Stimulation and Machine Learning.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Automated sleep detection in movement disorders may allow monitoring sleep, potentially guiding adaptive deep brain stimulation (DBS).