AIMC Topic: Stroke

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Relationships between motor and cognitive functions and subsequent post-stroke mood disorders revealed by machine learning analysis.

Scientific reports Nov 11, 2020
Mood disorders (e.g. depression, apathy, and anxiety) are often observed in stroke patients, exhibiting a negative impact on functional recovery associated with various physical disorders and cognitive dysfunction. Consequently, post-stroke symptoms ...
Movement Stroke Rehabilitation Female Aged Male Middle Aged ROC Curve Cognition Stroke Mood Disorders Humans Neural Networks, Computer Machine Learning
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Breaking the ice to improve motor outcomes in patients with chronic stroke: a retrospective clinical study on neuromodulation plus robotics.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Nov 6, 2020
BACKGROUND: Stroke is one of the main causes of impairment affecting daily activities and quality of life. There is a growing effort to potentiate the recovery of functional gait and to enable stroke patients to walk independently.
Robotics Stroke Gait Exercise Therapy Humans Retrospective Studies Quality of Life Stroke Rehabilitation Transcranial Direct Current Stimulation Gait Disorders, Neurologic
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Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning.

Neuroscience letters Nov 6, 2020
This study applied machine learning regression to predict motor function after stroke based on multimodal magnetic resonance imaging. Fifty-four stroke patients, who underwent T1 weighted, diffusion tensor, and resting state functional magnetic reson...
Aged Male Middle Aged Magnetic Resonance Imaging Brain Mapping Multimodal Imaging Stroke Machine Learning Brain Retrospective Studies Female Humans
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Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method.

Neurorehabilitation and neural repair Nov 5, 2020
BACKGROUND: Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results.
Machine Learning Female Aged Adult Humans Accelerometry Upper Extremity Stroke Rehabilitation Male Middle Aged Stroke
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Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Physics in medicine and biology Nov 5, 2020
Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke (AIS) patients. The aim of this paper is to develop an automated segmentation method for accurately segmenting follow-up ischemic and hemorrhagic les...
Female Male Image Processing, Computer-Assisted Stroke Humans Neural Networks, Computer Tomography, X-Ray Computed
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Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.

Journal of the American Heart Association Nov 3, 2020
Background Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community-based interventions have been shown to be both effective and cost-effective in preventing cardiovascul...
Socioeconomic Factors Residence Characteristics Age Factors Stroke Exercise Prevalence United States Machine Learning Female Health Behavior Risk Factors Aged Young Adult Adult Male Middle Aged Humans
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Wearable hip-assist robot modulates cortical activation during gait in stroke patients: a functional near-infrared spectroscopy study.

Journal of neuroengineering and rehabilitation Oct 29, 2020
BACKGROUND: Gait dysfunction is common in post-stroke patients as a result of impairment in cerebral gait mechanism. Powered robotic exoskeletons are promising tools to maximize neural recovery by delivering repetitive walking practice.
Stroke Rehabilitation Gait Disorders, Neurologic Gait Hip Humans Exoskeleton Device Male Brain Middle Aged Female Robotics Stroke
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Incorporating Artificial Intelligence Into Stroke Care and Research.

Stroke Oct 27, 2020
Neuroimaging Humans Neural Networks, Computer Artificial Intelligence Risk Assessment Prognosis Deep Learning Clinical Decision-Making User-Computer Interface Biomedical Research Stroke
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Robot-Assisted Arm Training versus Therapist-Mediated Training after Stroke: A Systematic Review and Meta-Analysis.

Journal of healthcare engineering Oct 27, 2020
BACKGROUND: More than two-thirds of stroke patients have arm motor impairments and function deficits on hospital admission, leading to diminished quality of life and reduced social participation. Robot-assisted training (RAT) is a promising rehabilit...
Stroke Humans Quality of Life Activities of Daily Living Robotics Arm Stroke Rehabilitation
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Robot-assisted Gait Training Using Welwalk in Hemiparetic Stroke Patients: An Effectiveness Study with Matched Control.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Oct 19, 2020
OBJECTIVE: Although studies on the efficacy of the rehabilitation robot are increasing, there are few reports using the robot for gait training in the actual clinical setting. This study aimed to investigate the effectiveness of gait training using W...
Middle Aged Time Factors Treatment Outcome Recovery of Function Robotics Disability Evaluation Stroke Retrospective Studies Gait Female Aged Male Stroke Rehabilitation Paresis Humans Exoskeleton Device Prospective Studies Motor Activity
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