AIMC Topic: Motor Disorders

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Convolutional Neural Network-Based Automated Segmentation of the Spinal Cord and Contusion Injury: Deep Learning Biomarker Correlates of Motor Impairment in Acute Spinal Cord Injury.

AJNR. American journal of neuroradiology Mar 28, 2019
BACKGROUND AND PURPOSE: Our aim was to use 2D convolutional neural networks for automatic segmentation of the spinal cord and traumatic contusion injury from axial T2-weighted MR imaging in a cohort of patients with acute spinal cord injury.
Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Deep Learning Motor Disorders Contusions Image Interpretation, Computer-Assisted Spinal Cord Injuries Humans Female
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In-home and remote use of robotic body surrogates by people with profound motor deficits.

PloS one Mar 15, 2019
By controlling robots comparable to the human body, people with profound motor deficits could potentially perform a variety of physical tasks for themselves, improving their quality of life. The extent to which this is achievable has been unclear due...
Internet Motor Disorders Robotics Equipment Design Time Factors Persons with Disabilities Male Middle Aged Quality of Life Virtual Reality Computers Self Care Humans
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Soft robotic devices for hand rehabilitation and assistance: a narrative review.

Journal of neuroengineering and rehabilitation Feb 17, 2018
INTRODUCTION: The debilitating effects on hand function from a number of a neurologic disorders has given rise to the development of rehabilitative robotic devices aimed at restoring hand function in these patients. To combat the shortcomings of prev...
Robotics Equipment Design Hand Exoskeleton Device Humans Motor Disorders
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Automatic recognition of gait patterns in human motor disorders using machine learning: A review.

Medical engineering & physics Jan 17, 2018
BACKGROUND: automatic recognition of human movement is an effective strategy to assess abnormal gait patterns. Machine learning approaches are mainly applied due to their ability to work with multidimensional nonlinear features.
Machine Learning Female Humans Motor Disorders Middle Aged Gait Adult Walking Automation Male
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Decoding post-stroke motor function from structural brain imaging.

NeuroImage. Clinical Aug 2, 2016
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine ...
Male Brain Magnetic Resonance Imaging Humans Middle Aged Motor Disorders Stroke Machine Learning Female
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A Deep Learning Approach for Grading of Motor Impairment Severity in Parkinson's Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's disease (PD). This study examined the ability of deep learning approaches to grade motor impairment seve...
Humans Movement Hypokinesia Motor Disorders Deep Learning Parkinson Disease
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Gait-assisted exoskeletons for children with cerebral palsy or spinal muscular atrophy: A systematic review.

NeuroRehabilitation Jan 1, 2021
BACKGROUND: Cerebral Palsy (CP) and Spinal Muscular Atrophy (SMA) are common causes of motor disability in childhood. Gait exoskeletons are currently being used as part of rehabilitation for children with walking difficulties.
Muscular Atrophy, Spinal Exoskeleton Device Motor Disorders Persons with Disabilities Robotics Child, Preschool Gait Humans Child Cerebral Palsy Adolescent
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