AIMC Topic: Stroke
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The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke.
Journal of neuroengineering and rehabilitation
Jan 27, 2023
BACKGROUND: Robots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical ordinal scales. Determining how to define the presence or absence of impairment in individuals using k...
Effect of cyborg-type robot Hybrid Assistive Limb on patients with severe walking disability in acute stroke: A randomized controlled study.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jan 24, 2023
OBJECTIVES: To investigate whether early gait training using Hybrid Assistive Limb (HAL) is feasible and improves walking and independency compared with conventional physical therapy (CPT) in patients with severe walking disability after stroke.
Deep learning-based personalised outcome prediction after acute ischaemic stroke.
Journal of neurology, neurosurgery, and psychiatry
Jan 17, 2023
BACKGROUND: Whether deep learning models using clinical data and brain imaging can predict the long-term risk of major adverse cerebro/cardiovascular events (MACE) after acute ischaemic stroke (AIS) at the individual level has not yet been studied.
Deep learning for collateral evaluation in ischemic stroke with imbalanced data.
International journal of computer assisted radiology and surgery
Jan 12, 2023
PURPOSE: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods...
Enhancing Free-Living Fall Risk Assessment: Contextualizing Mobility Based IMU Data.
Sensors (Basel, Switzerland)
Jan 12, 2023
Fall risk assessment needs contemporary approaches based on habitual data. Currently, inertial measurement unit (IMU)-based wearables are used to inform free-living spatio-temporal gait characteristics to inform mobility assessment. Typically, a fluc...
Head CT deep learning model is highly accurate for early infarct estimation.
Scientific reports
Jan 5, 2023
Non-contrast head CT (NCCT) is extremely insensitive for early (< 3-6 h) acute infarct identification. We developed a deep learning model that detects and delineates suspected early acute infarcts on NCCT, using diffusion MRI as ground truth (3566 NC...
Quo Vadis, Amadeo Hand Robot? A Randomized Study with a Hand Recovery Predictive Model in Subacute Stroke.
International journal of environmental research and public health
Dec 30, 2022
BACKGROUND: Early identification of hand-prognosis-factors at patient's admission could help to select optimal synergistic rehabilitation programs based on conventional (COHT) or robot-assisted (RAT) therapies.
Combined robot motor assistance with neural circuit-based virtual reality (NeuCir-VR) lower extremity rehabilitation training in patients after stroke: a study protocol for a single-centre randomised controlled trial.
BMJ open
Dec 23, 2022
INTRODUCTION: Improving lower extremity motor function is the focus and difficulty of post-stroke rehabilitation treatment. More recently, robot-assisted and virtual reality (VR) training are commonly used in post-stroke rehabilitation and are consid...
Immersive Virtual Reality during Robot-Assisted Gait Training: Validation of a New Device in Stroke Rehabilitation.
Medicina (Kaunas, Lithuania)
Dec 7, 2022
Background and objective: Duration of rehabilitation and active participation are crucial for gait rehabilitation in the early stage after stroke onset. Virtual reality (VR) is an innovative tool providing engaging and playful environments that could...
A Transferable Deep Learning Prognosis Model for Predicting Stroke Patients' Recovery in Different Rehabilitation Trainings.
IEEE journal of biomedical and health informatics
Dec 7, 2022
Since the underlying mechanisms of neurorehabilitation are not fully understood, the prognosis of stroke recovery faces significant difficulties. Recovery outcomes can vary when undergoing different treatments; however, few models have been developed...
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