AIMC Topic: Stroke
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Explainable Deep-Learning Prediction for Brain-Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 12, 2024
Predicting the potential for recovery of motor function in stroke patients who undergo specific rehabilitation treatments is an important and major challenge. Recently, electroencephalography (EEG) has shown potential in helping to determine the rela...
Machine learning applied to gait analysis data in cerebral palsy and stroke: A systematic review.
Gait & posture
Apr 10, 2024
BACKGROUND: Among neurological pathologies, cerebral palsy and stroke are the main contributors to walking disorders. Machine learning methods have been proposed in the recent literature to analyze gait data from these patients. However, machine lear...
A Comprehensive Review: Robot-Assisted Treatments for Gait Rehabilitation in Stroke Patients.
Medicina (Kaunas, Lithuania)
Apr 10, 2024
Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a groundbreaking method to improve motor recovery and enhance the quality of life for stroke survivors. This review investigates the effectiveness and appli...
Impaired proprioception and magnified scaling of proprioceptive error responses in chronic stroke.
Journal of neuroengineering and rehabilitation
Apr 9, 2024
BACKGROUND: Previous work has shown that ~ 50-60% of individuals have impaired proprioception after stroke. Typically, these studies have identified proprioceptive impairments using a narrow range of reference movements. While this has been important...
Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience.
Journal of neuroengineering and rehabilitation
Apr 9, 2024
BACKGROUND: Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the un...
A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes.
AJNR. American journal of neuroradiology
Apr 8, 2024
BACKGROUND AND PURPOSE: Predicting long-term clinical outcome in acute ischemic stroke is beneficial for prognosis, clinical trial design, resource management, and patient expectations. This study used a deep learning-based predictive model (DLPD) to...
Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.
Medical & biological engineering & computing
Apr 5, 2024
Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although previous studies have demonstrated that machine learning (ML) shows reasonably accurate stroke outco...
Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review.
Journal of neural engineering
Apr 3, 2024
. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Literature has consistently shown that early and intensive rehabilitation is beneficial for stroke patients. Robot-assisted devices have been extensively st...
PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.
Stroke
Mar 28, 2024
BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized prediction may improve stroke survivors' engagement in self-care. We developed PRERISK: a statistical and machine learning classifier to predict individ...
Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.
Journal of clinical hypertension (Greenwich, Conn.)
Mar 24, 2024
Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment with three antihypertensives, is associated with an increased risk of developing cardiovascular and re...
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